geofeed-tuner

分类: 测试与安全 | 上传者: fastah | 下载: 0 | 版本: v1.0（最新）
Use this skill whenever the user mentions IP geolocation feeds, RFC 8805, geofeeds, inetnum, inet6num, CIDR subnets, or wants help creating, tuning, validating, or publishing a self-published IP geolocation feed in CSV format. Also trigger when the user is a network operator, ISP, mobile carrier, cloud provider, hosting company, IXP, or satellite provider asking about IP geolocation accuracy, prefix mapping, or WHOIS geofeed attributes. Helps create, refine, and improve CSV-format IP geolocation feeds with opinionated recommendations beyond RFC 8805 compliance. Do NOT use for private or internal IP address management — applies only to publicly routable IP addresses.
更新日志: Source: GitHub https://github.com/fastah/ip-geofeed-skills
目录结构

当前层级: skills/geofeed-tuner/
📁 assets/
- 📁 example/
  - 📄 01-user-input-rfc8805-feed.csv 214 B
- 📄 iso3166-1.json 42.3 KB
- 📄 iso3166-2.json 486.4 KB
- 📄 small-territories.json 1.0 KB
📁 references/
- 📄 rfc8805.txt 40.4 KB
- 📄 snippets-python3.md 3.4 KB
📁 run/
- 📄 .gitignore 14 B
📁 scripts/
- 📁 templates/
  - 📄 index.html 147.4 KB
- 📄 .gitkeep 0 B
📄 SKILL.md 38.8 KB
SKILL.md

---
name: geofeed-tuner
description: >
  Use this skill whenever the user mentions IP geolocation feeds, RFC 8805, geofeeds, inetnum,
  inet6num, CIDR subnets, or wants help creating, tuning, validating, or publishing a
  self-published IP geolocation feed in CSV format. Also trigger when the user is a network
  operator, ISP, mobile carrier, cloud provider, hosting company, IXP, or satellite provider
  asking about IP geolocation accuracy, prefix mapping, or WHOIS geofeed attributes.
  Helps create, refine, and improve CSV-format IP geolocation feeds with opinionated
  recommendations beyond RFC 8805 compliance. Do NOT use for private or internal IP address
  management — applies only to publicly routable IP addresses.
license: Apache-2.0
metadata:
  author: Sid Mathur <support@getfastah.com>
  version: "0.4"
compatibility: Requires Python 3
---

# Geofeed Tuner – Create Better IP Geolocation Feeds

This skill helps you create and improve IP geolocation feeds in CSV format by:
- Ensuring your CSV is well-formed and consistent
- Checking alignment with [RFC 8805](references/rfc8805.txt) (the industry standard)
- Applying **opinionated best practices** learned from real-world deployments
- Suggesting improvements for accuracy, completeness, and privacy

## When to Use This Skill

- Use this skill when a user asks for help **creating, improving, or publishing** an IP geolocation feed file in CSV format.
- Use it to **tune and troubleshoot CSV geolocation feeds** — catching errors, suggesting improvements, and ensuring real-world usability beyond RFC compliance.
- **Intended audience:**
  - Network operators, administrators, and engineers responsible for publicly routable IP address space
  - Organizations such as ISPs, mobile carriers, cloud providers, hosting and colocation companies, Internet Exchange operators, and satellite internet providers
- **Do not use** this skill for private or internal IP address management; it applies **only to publicly routable IP addresses**.

## Prerequisites

- **Python 3** is required.

## Directory Structure and File Management

This skill uses a clear separation between **distribution files** (read-only) and **working files** (generated at runtime).

### Read-Only Directories (Do Not Modify)

The following directories contain static distribution assets. **Do not create, modify, or delete files in these directories:**

| Directory      | Purpose                                                    |
|----------------|------------------------------------------------------------|
| `assets/`      | Static data files (ISO codes, examples)                    |
| `references/`  | RFC specifications and code snippets for reference         |
| `scripts/`     | Executable code and HTML template files for reports        |

### Working Directories (Generated Content)

All generated, temporary, and output files go in these directories:

| Directory       | Purpose                                              |
|-----------------|------------------------------------------------------|
| `run/`          | Working directory for all agent-generated content    |
| `run/data/`     | Downloaded CSV files from remote URLs                |
| `run/report/`   | Generated HTML tuning reports                        |

### File Management Rules

1. **Never write to `assets/`, `references/`, or `scripts/`** — these are part of the skill distribution and must remain unchanged.
2. **All downloaded input files** (from remote URLs) must be saved to `./run/data/`.
3. **All generated HTML reports** must be saved to `./run/report/`.
4. **All generated Python scripts** must be saved to `./run/`.
5. The `run/` directory may be cleared between sessions; do not store permanent data there.
6. **Working directory for execution:** All generated scripts in `./run/` must be executed with the **skill root directory** (the directory containing `SKILL.md`) as the current working directory, so that relative paths like `assets/iso3166-1.json` and `./run/data/report-data.json` resolve correctly. Do not `cd` into `./run/` before running scripts.


## Processing Pipeline: Sequential Phase Execution

All phases must be executed **in order**, from Phase 1 through Phase 6. Each phase depends on the successful completion of the previous phase. For example, **structure checks** must complete before **quality analysis** can run.

The phases are summarized below. The agent must follow the detailed steps outlined further in each phase section.

| Phase | Name                       | Description                                                                       |
|-------|----------------------------|-----------------------------------------------------------------------------------|
| 1     | Understand the Standard    | Review the key requirements of RFC 8805 for self-published IP geolocation feeds   |
| 2     | Gather Input               | Collect IP subnet data from local files or remote URLs                            |
| 3     | Checks & Suggestions       | Validate CSV structure, analyze IP prefixes, and check data quality               |
| 4     | Tuning Data Lookup         | Use Fastah's MCP tool to retrieve tuning data for improving geolocation accuracy  |
| 5     | Generate Tuning Report     | Create an HTML report summarizing the analysis and suggestions                    |
| 6     | Final Review               | Verify consistency and completeness of the report data                            |

**Do not skip phases.** Each phase provides critical checks or data transformations required by subsequent stages.


### Execution Plan Rules

Before executing each phase, the agent MUST generate a visible TODO checklist.

The plan MUST:
- Appear at the very start of the phase
- List every step in order
- Use a checkbox format
- Be updated live as steps complete


### Phase 1: Understand the Standard

The key requirements from RFC 8805 that this skill enforces are summarized below. **Use this summary as your working reference.** Only consult the full [RFC 8805 text](references/rfc8805.txt) for edge cases, ambiguous situations, or when the user asks a standards question not covered here.

#### RFC 8805 Key Facts

**Purpose:** A self-published IP geolocation feed lets network operators publish authoritative location data for their IP address space in a simple CSV format, allowing geolocation providers to incorporate operator-supplied corrections.

**CSV Column Order (Sections 2.1.1.1–2.1.1.5):**

| Column | Field         | Required | Notes                                                      |
|--------|---------------|----------|------------------------------------------------------------|
| 1      | `ip_prefix`   | Yes      | CIDR notation; IPv4 or IPv6; must be a network address     |
| 2      | `alpha2code`  | No       | ISO 3166-1 alpha-2 country code; empty = do-not-geolocate |
| 3      | `region`      | No       | ISO 3166-2 subdivision code (e.g., `US-CA`)               |
| 4      | `city`        | No       | Free-text city name; no authoritative validation set       |
| 5      | `postal_code` | No       | **Deprecated** — must be left empty or absent             |

**Structural rules:**
- Files may contain comment lines beginning with `#` (including the header, if present).
- A header row is optional; if present, it is treated as a comment if it starts with `#`.
- Files must be encoded in UTF-8.
- Subnet host bits must not be set (i.e., `192.168.1.1/24` is invalid; use `192.168.1.0/24`).
- Applies only to **globally routable** unicast addresses — not private, loopback, link-local, or multicast space.

**Do-not-geolocate:** An entry with an empty `alpha2code` (and empty region/city) is an explicit signal that the operator does not want geolocation applied to that prefix.

**Postal codes deprecated (Section 2.1.1.5):** The fifth column must not contain postal or ZIP codes. They are too fine-grained for IP-range mapping and raise privacy concerns.


### Phase 2: Gather Input

- If the user has not already provided a list of IP subnets or ranges (sometimes referred to as `inetnum` or `inet6num`), prompt them to supply it. Accepted input formats:
  - Text pasted into the chat
  - A local CSV file
  - A remote URL pointing to a CSV file

- If the input is a **remote URL**:
  - Attempt to download the CSV file to `./run/data/` before processing.
  - On HTTP error (4xx, 5xx, timeout, or redirect loop), **stop immediately** and report to the user:
    `Feed URL is not reachable: HTTP {status_code}. Please verify the URL is publicly accessible.`
  - Do not proceed to Phase 3 with an incomplete or empty download.

- If the input is a **local file**, process it directly without downloading.

- **Encoding detection and normalization:**
  1. Attempt to read the file as UTF-8 first.
  2. If a `UnicodeDecodeError` is raised, try `utf-8-sig` (UTF-8 with BOM), then `latin-1`.
  3. Once successfully decoded, re-encode and write the working copy as UTF-8.
  4. If no encoding succeeds, stop and report: `Unable to decode input file. Please save it as UTF-8 and try again.`


### Phase 3: Checks & Suggestions

#### Execution Rules
- Generate **exactly one script** for this phase.
- Do NOT combine this phase with others.
- Do NOT precompute future-phase data.
- Store the output as a JSON file at: [`./run/data/report-data.json`](./run/data/report-data.json)

#### Schema Definition

The JSON structure below is **IMMUTABLE** during Phase 3. Phase 4 will later add a `tuned_entries` array to each object in `entries` — this is the only permitted schema extension and happens in a separate phase.

```json
{
  "input_file": "",
  "timestamp": 0,

  "total_entries": 0,
  "ipv4_entries": 0,
  "ipv6_entries": 0,
  "invalid_entries": 0,

  "error_count": 0,
  "warning_count": 0,
  "ok_count": 0,
  "suggestion_count": 0,

  "city_level_accuracy": 0,
  "region_level_accuracy": 0,
  "country_level_accuracy": 0,
  "do_not_geolocate_entries": 0,

  "entries": [
    {
      "line": 0,
      "ip_prefix": "",
      "country": "",
      "region": "",
      "city": "",

      "status": "",

      "messages": [
        {
          "status": "",
          "message": ""
        }
      ],

      "has_error": false,
      "has_warning": false,
      "has_suggestion": false,
      "need_region": false,
      "is_small_territory": false
    }
  ]
}
```

Field definitions:
- `input_file`: The original input source, either a local filename or a remote URL.
- `timestamp`: Milliseconds since Unix epoch when the tuning was performed.
- `total_entries`: Total number of data rows processed (excluding comment and blank lines).
- `ipv4_entries`: Count of entries that are IPv4 subnets.
- `ipv6_entries`: Count of entries that are IPv6 subnets.
- `invalid_entries`: Count of entries that failed IP prefix parsing.
- `error_count`: Total entries whose `status` is `ERROR`.
- `warning_count`: Total entries whose `status` is `WARNING`.
- `ok_count`: Total entries whose `status` is `OK`.
- `suggestion_count`: Total entries whose `status` is `SUGGESTION`.
- `city_level_accuracy`: Count of valid entries where `city` is non-empty.
- `region_level_accuracy`: Count of valid entries where `region` is non-empty and `city` is empty.
- `country_level_accuracy`: Count of valid entries where `country` is non-empty, `region` is empty, and `city` is empty.
- `do_not_geolocate_entries`: Count of valid entries where `country`, `region`, and `city` are all empty.
- `entries`: Array of objects, one per data row, with the following per-entry fields:
  - `line`: 1-based line number in the original CSV (counting all lines including comments and blanks).
  - `ip_prefix`: The normalized IP prefix in CIDR slash notation.
  - `country`: The ISO 3166-1 alpha-2 country code, or empty string.
  - `region`: The ISO 3166-2 region code (e.g., `US-CA`), or empty string.
  - `city`: The city name, or empty string.
  - `status`: Highest severity assigned: `ERROR` > `WARNING` > `SUGGESTION` > `OK`.
  - `messages`: Array of `{ "status": "...", "message": "..." }` validation messages.
  - `has_error`: `true` if any message has status `ERROR`.
  - `has_warning`: `true` if any message has status `WARNING`.
  - `has_suggestion`: `true` if any message has status `SUGGESTION`.
  - `need_region`: `true` if the entry triggered the "missing region when city is specified" suggestion.
  - `is_small_territory`: `true` if the country is classified as a small territory per `assets/small-territories.json`.

#### Accuracy Level Counting Rules

Accuracy levels are **mutually exclusive**. Assign each valid (non-ERROR, non-invalid) entry to exactly one bucket based on the most granular non-empty geo field:

| Condition                                       | Bucket                     |
|-------------------------------------------------|----------------------------|
| `city` is non-empty                             | `city_level_accuracy`      |
| `region` non-empty AND `city` is empty          | `region_level_accuracy`    |
| `country` non-empty, `region` and `city` empty  | `country_level_accuracy`   |
| All three fields (`country`, `region`, `city`) empty | `do_not_geolocate_entries` |

**Do not count** entries with `has_error: true` or entries in `invalid_entries` in any accuracy bucket.

The agent MUST NOT:
- Rename fields
- Add or remove fields
- Change data types
- Reorder keys
- Alter nesting
- Wrap the object
- Split into multiple files

If a value is unknown, **leave it empty** — never invent data.

#### Structure & Format Check

This phase verifies that your feed is well-formed and parseable. **Critical structural errors** must be resolved before the tuner can analyze geolocation quality.

##### CSV Structure

This subsection defines rules for **CSV-formatted input files** used for IP geolocation feeds.
The goal is to ensure the file can be parsed reliably and normalized into a **consistent internal representation**.

- **CSV Structure Checks**
  - If `pandas` is available, use it for CSV parsing.
  - Otherwise, fall back to Python's built-in `csv` module.

  - Ensure the CSV contains **exactly 4 or 5 logical columns**.
  - Comment lines are allowed.
  - A header row **may or may not** be present.
  - If no header row exists, assume the implicit column order:
    ```
    ip_prefix, alpha2code, region, city, postal code (deprecated)
    ```
  - Refer to the example input file:
    [`assets/example/01-user-input-rfc8805-feed.csv`](assets/example/01-user-input-rfc8805-feed.csv)

- **CSV Cleansing and Normalization**
  - Clean and normalize the CSV using Python logic equivalent to the following operations:
    - Select only the **first five columns**, dropping any columns beyond the fifth.
    - Write the output file with a **UTF-8 BOM**.

  - **Comments**
    - Remove comment rows where the **first column begins with `#`**.
    - This also removes a header row if it begins with `#`.
    - Create a map of comments using the **1-based line number** as the key and the full original line as the value. Also store blank lines.
    - Store this map in a JSON file at: [`./run/data/comments.json`](./run/data/comments.json)
    - Example: `{ "4": "# It's OK for small city states to leave state ISO2 code unspecified" }`

- **Notes**
  - Both implementation paths (`pandas` and built-in `csv`) must write output using
    the `utf-8-sig` encoding to ensure a **UTF-8 BOM** is present.

#### IP Prefix Analysis
  - Check that the `ip_prefix` field is present and non-empty for each entry.
  - Check for duplicate `ip_prefix` values across entries.
  - If duplicates are found, stop the skill and report to the user with the message: `Duplicate IP prefix detected: {ip_prefix_value} appears on lines {line_numbers}`
  - If no duplicates are found, continue with the analysis.

  - **Checks**
    - Each subnet must parse cleanly as either an **IPv4 or IPv6 network** using the code snippets in the `references/` folder.
    - Subnets must be normalized and displayed in **CIDR slash notation**.
      - Single-host IPv4 subnets must be represented as **`/32`**.
      - Single-host IPv6 subnets must be represented as **`/128`**.

  - **ERROR**
    - Report the following conditions as **ERROR**:

    - **Invalid subnet syntax**
      - Message: `Invalid IP prefix: unable to parse as IPv4 or IPv6 network`

    - **Non-public address space**
      - Applies to subnets that are **private, loopback, link-local, multicast, or otherwise non-public**
        - In Python, detect non-public ranges using `is_private` and related address properties as shown in `./references`.
      - Message: `Non-public IP range is not allowed in an RFC 8805 feed`

    - **RFC 8805–incompatible subnet**
      - Any subnet failing mandatory RFC 8805 constraints
      - Message: `Subnet is not valid for publication in an RFC 8805 geofeed`

  - **SUGGESTION**
    - Report the following conditions as **SUGGESTION**:

    - **Overly large IPv6 subnets**
      - Prefixes shorter than `/64`
      - Message: `IPv6 prefix is unusually large and may indicate a typo`

    - **Overly large IPv4 subnets**
      - Prefixes shorter than `/22`
      - Message: `IPv4 prefix is unusually large and may indicate a typo`

#### Geolocation Quality Check

Analyze the **accuracy and consistency** of geolocation data:
  - Country codes
  - Region codes
  - City names
  - Deprecated fields

This phase runs after structural checks pass.

##### Country Code Analysis
  - Use the locally available data table [`ISO3166-1`](assets/iso3166-1.json) for checking.
    - JSON array of countries and territories with ISO codes
    - Each object includes:
      - `alpha_2`: two-letter country code
      - `name`: short country name
      - `flag`: flag emoji
    - This file represents the **superset of valid `alpha2code` values** for an RFC 8805 CSV.
  - Check `alpha2code` (RFC 8805 Section 2.1.1.2) against the `alpha_2` attribute.
  - Sample code is available in the `references/` directory.

  - If a country is found in [`assets/small-territories.json`](assets/small-territories.json), set `is_small_territory` to `true`. This value is used in later checks and suggestions related to small territories.

  - **Note:** `small-territories.json` contains some historic/disputed codes (`AN`, `CS`, `XK`) that are not present in `iso3166-1.json`. An entry using one of these as its `alpha2code` will fail the country code validation (ERROR) even though it matches as a small territory. The country code ERROR takes precedence — do not suppress it based on the small-territory flag.

  - **ERROR**
    - Report the following conditions as **ERROR**:
    - **Invalid country code**
      - Condition: `alpha2code` is present but not found in the `alpha_2` set
      - Message: `Invalid country code: not a valid ISO 3166-1 alpha-2 value`

##### Region Code Analysis
  - Use the locally available data table [`ISO3166-2`](assets/iso3166-2.json) for checking.
    - JSON array of country subdivisions with ISO-assigned codes
    - Each object includes:
      - `code`: subdivision code prefixed with country code (e.g., `US-CA`)
      - `name`: short subdivision name
    - This file represents the **superset of valid `region` values** for an RFC 8805 CSV.
  - If a `region` value is provided (RFC 8805 Section 2.1.1.3):
    - Check that the format matches `{COUNTRY}-{SUBDIVISION}` (e.g., `US-CA`, `AU-NSW`).
    - Check the value against the `code` attribute (already prefixed with the country code).

  - **Small-territory exception:** If `is_small_territory` is `true` **and** the `region` value equals the entry's `alpha2code` (e.g., `SG` as both country and region for Singapore), treat the region as acceptable — skip all region validation checks for this entry. Small territories are effectively city-states with no meaningful ISO 3166-2 administrative subdivisions.

  - **ERROR**
    - Report the following conditions as **ERROR**:
    - **Invalid region format**
      - Condition: `region` does not match `{COUNTRY}-{SUBDIVISION}` **and** the small-territory exception does not apply
      - Message: `Invalid region format; expected COUNTRY-SUBDIVISION (e.g., US-CA)`
    - **Unknown region code**
      - Condition: `region` value is not found in the `code` set **and** the small-territory exception does not apply
      - Message: `Invalid region code: not a valid ISO 3166-2 subdivision`
    - **Country–region mismatch**
      - Condition: Country portion of `region` does not match `alpha2code`
      - Message: `Region code does not match the specified country code`

##### City Name Analysis

  - City names are validated using **heuristic checks only**.
  - There is currently **no authoritative dataset** available for validating city names.

  - **ERROR**
    - Report the following conditions as **ERROR**:
    - **Placeholder or non-meaningful values**
      - Condition: Placeholder or non-meaningful values including but not limited to:
        - `undefined`
        - `Please select`
        - `null`
        - `N/A`
        - `TBD`
        - `unknown`
      - Message: `Invalid city name: placeholder value is not allowed`

    - **Truncated names, abbreviations, or airport codes**
      - Condition: Truncated names, abbreviations, or airport codes that do not represent valid city names:
        - `LA`
        - `Frft`
        - `sin01`
        - `LHR`
        - `SIN`
        - `MAA`
      - Message: `Invalid city name: abbreviated or code-based value detected`

  - **WARNING**
    - Report the following conditions as **WARNING**:
    - **Inconsistent casing or formatting**
      - Condition: City names with inconsistent casing, spacing, or formatting that may reduce data quality, for example:
        - `HongKong` vs `Hong Kong`
        - Mixed casing or unexpected script usage
      - Message: `City name formatting is inconsistent; consider normalizing the value`

##### Postal Code Check
  - RFC 8805 Section 2.1.1.5 explicitly **deprecates postal or ZIP codes**.
  - Postal codes can represent very small populations and are **not considered privacy-safe** for mapping IP address ranges, which are statistical in nature.

  - **ERROR**
    - Report the following conditions as **ERROR**:
    - **Postal code present**
      - Condition: A non-empty value is present in the postal/ZIP code field.
      - Message: `Postal codes are deprecated by RFC 8805 and must be removed for privacy reasons`

#### Tuning & Recommendations

This phase applies **opinionated recommendations** beyond RFC 8805, learned from real-world geofeed deployments, that improve accuracy and usability.

- **SUGGESTION**
  - Report the following conditions as **SUGGESTION**:

  - **Region or city specified for small territory**
    - Condition:
      - `is_small_territory` is `true`
      - `region` is non-empty **OR**
      - `city` is non-empty.
    - Message: `Region or City-level granularity is usually unnecessary for small territories; consider removing the region and city values`

  - **Missing region code when city is specified**
    - Condition:
      - `city` is non-empty
      - `region` is empty
      - `is_small_territory` is `false`
    - Action: Set `need_region = true`
    - Message: `Region code is recommended when a city is specified; consider adding the appropriate region code for better accuracy`

  - **Unspecified geolocation for subnet**
    - Condition: All geographical fields (`alpha2code`, `region`, `city`) are empty for a subnet.
    - Message: `Confirm whether this subnet is intentionally marked as do-not-geolocate or missing location data`


### Phase 4: Tuning Data Lookup

#### Objective
Lookup all the entries in the file using Fastah's `rfc8805-row-place-search` tool.

#### Execution Rules
- Use a **separate script** _only_ for payload generation (read the dataset and write one or more payload JSON files; do not call MCP from this script).
- Server only accepts 1000 entries per request, so if there are more than 1000 entries, split into multiple requests.
- The agent must read the generated payload files, construct the requests from them, and send those requests to the MCP server in batches of at most 1000 entries each.
- **On MCP failure:** If the MCP server is unreachable, returns an error, or returns no results for any batch, log a warning and continue to Phase 5. Set `tuned_entries: []` for all affected entries. Do not block report generation. Notify the user clearly: `Tuning data lookup unavailable; the report will show validation results only.`
- Suggestions are **advisory only** — **never auto-populate** them.

#### Step 1: Load Dataset
Load the dataset from: [./run/data/report-data.json](./run/data/report-data.json)
- Read the `entries` array.
- Include all entries.

#### Step 2: Build Lookup Payload with Deduplication

Reduce server requests by deduplicating identical entries:
- For each entry in `entries`, compute a content hash (hash of countryCode + regionCode + cityName).
- Create a deduplication map: `{ contentHash -> { rowKey, payload, entryIndices: [] } }`. rowKey is a UUID that will be sent to the MCP server for matching responses.
- If an entry's hash already exists, append its **0-based array index** in `entries` to that deduplication entry's `entryIndices` array.
- If hash is new, generate a **UUID (rowKey)** and create a new deduplication entry.

Build request batches:
- Extract unique deduplicated entries from the map, keeping them in deduplication order.
- Build request batches of up to 1000 items each.
- For each batch, keep an in-memory structure like `[{ rowKey, payload, entryIndices }, ...]` to match responses back by rowKey.
- When writing the MCP payload file, include the `rowKey` field with each payload object:

```json
[
    {"rowKey": "550e8400-e29b-41d4-a716-446655440000", "countryCode":"CA","regionCode":"CA-ON","cityName":"Toronto"},
    {"rowKey": "6ba7b810-9dad-11d1-80b4-00c04fd430c8", "countryCode":"IN","regionCode":"IN-KA","cityName":"Bangalore"},
    {"rowKey": "6ba7b811-9dad-11d1-80b4-00c04fd430c8", "countryCode":"IN","regionCode":"IN-KA"}
]
```

- When reading responses, match each response `rowKey` field to the corresponding deduplication entry to retrieve all associated `entryIndices`.

Rules:
- Write payload to: [./run/data/mcp-server-payload.json](./run/data/mcp-server-payload.json)
- Exit the script after writing the payload.

#### Step 3: Invoke Fastah MCP Tool

- An example `mcp.json` style configuration of Fastah MCP server is as follows:
```json
    "fastah-ip-geofeed": {
      "type": "http",
      "url": "https://mcp.fastah.ai/mcp"
    }
```
- Server: `https://mcp.fastah.ai/mcp`
- Tool: `rfc8805-row-place-search`
- Open [./run/data/mcp-server-payload.json](./run/data/mcp-server-payload.json) and send all deduplicated entries with their rowKeys.
- If there are more than 1000 deduplicated entries after deduplication, split into multiple requests of 1000 entries each.
- The server will respond with the same `rowKey` field in each response for mapping back.
- Do NOT use local data.

#### Step 4: Attach Tuned Data to Entries

- Use a **separate script** for attaching tuned data.
- Load both [./run/data/report-data.json](./run/data/report-data.json) and the deduplication map (held in memory from Step 2, or re-derived from the payload file).
- For each response from the MCP server:
  - Extract the `rowKey` from the response.
  - Look up the `entryIndices` array associated with that `rowKey` from the deduplication map.
  - For each index in `entryIndices`, attach the normalized suggestions to `entries[index]`.
- Keep **at least three suggestions** when available.
- If fewer than three exist, keep all returned values.

Create the field on each affected entry if it does not exist:

```json
"tuned_entries": [
  {
    "placeName": "",
    "countryCode": "",
    "regionCode": "",
    "placeType": "",
    "h3Cells": [],
    "boundingBox": []
  }
]
```

Entries with no UUID match (i.e. the MCP server returned no response for their UUID) must receive an empty `tuned_entries: []` array — never leave the field absent.

#### Step 5: Store Updated Dataset

- Write the dataset back to: [./run/data/report-data.json](./run/data/report-data.json)
- Rules:
  - Maintain all existing validation flags.
  - Do NOT create additional intermediate files.


### Phase 5: Generate Tuning Report

Generate a **self-contained HTML report** by injecting data from `./run/data/report-data.json` and `./run/data/comments.json` into the template at `./scripts/templates/index.html`.

Write the completed report to `./run/report/geofeed-report.html`. After generating, attempt to open it in the system's default browser (e.g., `webbrowser.open()`). If running in a headless environment, CI pipeline, or remote container where no browser is available, skip the browser step and instead present the file path to the user so they can open or download it.

**Do not hand-write HTML for individual rows.** Write a Python script that reads the data files and produces the final HTML. Do not modify any CSS, JavaScript, or structural HTML in the template outside the injection points described below.

#### Step 1: Inject Summary Metadata

Replace the hardcoded values in the following elements by string substitution. All values come from `report-data.json` top-level fields.

**Implementation note:** The template contains **pre-filled placeholder values** (e.g., `<span id="errorCountMetrics">0</span>`, `<span id="suggestionsMetrics">21</span>`) that differ per element. Use a regex pattern like `(<span id="{element_id}">)(.*?)(</span>)` to replace the inner text regardless of the existing content. Do not hardcode the old values.

| Element (by `id`)        | Source field            | Notes                                                         |
|--------------------------|-------------------------|---------------------------------------------------------------|
| `#inputFileMetrics`      | `input_file`            | Replace inner text of the `<span>`                           |
| timestamp `<script>`     | `timestamp`             | Replace only the integer `1773720806552` with the actual value|
| `#totalEntriesMetrics`   | `total_entries`         | Replace inner text of the `<span>`                           |
| `#ipv4EntriesMetrics`    | `ipv4_entries`          | Replace inner text of the `<span>`                           |
| `#ipv6EntriesMetrics`    | `ipv6_entries`          | Replace inner text of the `<span>`                           |
| `#invalidEntriesMetrics` | `invalid_entries`       | Replace inner text of the `<span>`                           |
| `#errorCountMetrics`     | `error_count`           | Replace inner text of the `<span>`                           |
| `#warningCountMetrics`   | `warning_count`         | Replace inner text of the `<span>`                           |
| `#suggestionsMetrics`    | `suggestion_count`      | Replace inner text of the `<span>`                           |
| `#okCountMetrics`        | `ok_count`              | Replace inner text of the `<span>`                           |
| `#cityAccuracy`          | `city_level_accuracy`   | Replace inner text of the `<span>`                           |
| `#regionAccuracy`        | `region_level_accuracy` | Replace inner text of the `<span>`                           |
| `#countryAccuracy`       | `country_level_accuracy`| Replace inner text of the `<span>`                           |
| `#doNotGeolocate`        | `do_not_geolocate_entries` | Replace inner text of the `<span>`                        |

The timestamp element requires special treatment. Find this exact pattern in the template and replace only the integer literal:
```html
new Date( 1773720806552 )
```
Replace with:
```html
new Date( {timestamp} )
```
where `{timestamp}` is the integer millisecond epoch value from `report-data.json`.

#### Step 2: Inject the Comment Map

Locate this exact literal string in the template:
```javascript
const commentMap = JSON.parse('{}');
```
Replace the `'{}'` portion with the serialized, single-quote-safe JSON string of the comments map loaded from `./run/data/comments.json`. The result must be syntactically valid JavaScript — escape any single quotes inside comment text:
```javascript
const commentMap = JSON.parse('{...escaped JSON string...}');
```

#### Step 3: Generate and Inject Row HTML

Replace the entire content of `<tbody id="entriesTableBody">` with generated rows. For each entry in `report-data.json`'s `entries` array, generate **three consecutive `<tr>` elements**:

**Row 1 — Data row:**
```html
<tr
 id="csv-r-{line}"
 class="expandable-row"
 data-geocoding-hint=""
 data-do-not-geolocate="{true if country+region+city all empty, else false}"
 data-has-warning="{has_warning}"
 data-has-error="{has_error}"
 data-has-suggestion="{has_suggestion}"
 data-tunable="{true if tuned_entries is non-empty, else false}"
 data-tuned-country="{tuned_entries[0].countryCode or ''}"
 data-tuned-region="{tuned_entries[0].regionCode or ''}"
 data-tuned-city="{tuned_entries[0].placeName or ''}"
 data-h3-cells="{bracket-wrapped space-separated h3Cells from tuned_entries[0], or '[]'}"
 data-bounding-box="{bracket-wrapped space-separated boundingBox from tuned_entries[0], or '[]'}">
    <td><input type="checkbox" class="row-checkbox" checked></td>
    <td>{line}</td>
    <td><span class="status-badge status-{status.lower()}">{status_icon}{status}</span></td>
    <td><strong>{ip_prefix}</strong></td>
    <td>{country}</td>
    <td>{region}</td>
    <td>{city}</td>
</tr>
```

Status badge icons — use exactly this markup per status:

| `status`     | CSS class on `<span>`      | Icon `<i>` markup                                         |
|--------------|----------------------------|-----------------------------------------------------------|
| `OK`         | `status-ok`                | `<i class="bi bi-check-circle-fill"></i>`                 |
| `WARNING`    | `status-warning`           | `<i class="bi bi-exclamation-triangle-fill"></i>`         |
| `ERROR`      | `status-error`             | `<i class="bi bi-x-circle-fill"></i>`                     |
| `SUGGESTION` | `status-suggestion`        | `<i class="bi bi-lightbulb-fill"></i>`                    |

`data-tunable` must be the string `"true"` only when `tuned_entries` is present and has at least one element — this is what allows the "Tune All" button to apply suggested values to the row.

**Important: `data-h3-cells` and `data-bounding-box` format.** These are **NOT JSON arrays**. They are bracket-wrapped, space-separated values. The template JavaScript strips brackets with a regex and splits on whitespace/commas. Do **not** use JSON serialization (no quotes around string elements, no commas between numbers). Examples:
- `data-h3-cells="[836752fffffffff 836755fffffffff]"` — correct
- `data-h3-cells="["836752fffffffff","836755fffffffff"]"` — **WRONG**, quotes will break parsing
- `data-bounding-box="[-71.70 10.73 -71.52 10.55]"` — correct (west north east south, space-separated)
- `data-bounding-box="[-71.70, 10.73, -71.52, 10.55]"` — also works (commas tolerated) but spaces-only matches the template convention
- Empty: use `"[]"` for both attributes when no tuning data is available.

**Row 2 — Previous-values row:**
```html
<tr class="expand-details-row previous-values-row">
    <td></td>
    <td></td>
    <td></td>
    <td><strong>Previous values:</strong></td>
    <td class="previous-value"><span class="default-country">{country}</span></td>
    <td class="previous-value"><span class="default-region">{region}</span></td>
    <td class="previous-value"><span class="default-city">{city}</span></td>
</tr>
```

**Row 3 — Issues row:**
```html
<tr class="expand-details-row issues-row">
    <td></td>
    <td></td>
    <td colspan="5">
        <div class="issues-header">
            <strong>Issues:</strong>
            <button class="tune-all-btn" onclick="handleTuneButtonClick(this)">Tune</button>
        </div>
        {message_lines}
    </td>
</tr>
```

For each message in the entry's `messages` array, generate one `<div>`:
```html
<div class="message-line" data-id="{line * 100 + message_index}">
    <span>{message.message}</span>
    <input type="checkbox" disabled>
</div>
```
Use `message_index` as the 0-based position of the message within the entry's `messages` list. If `messages` is empty, omit the message divs — leave only the issues header `<div>`.

#### Output Guarantees

- The report must be readable in any modern browser without extra network dependencies beyond the CDN links already in the template (`leaflet`, `h3-js`, `bootstrap-icons`, Raleway font).
- All values embedded in HTML must be **HTML-escaped** (`<`, `>`, `&`, `"`) to prevent rendering issues.
- All values embedded inside JavaScript string literals (e.g., `commentMap`) must be **JSON-string-escaped**.
- All values must be derived **only from analysis output**, not recomputed heuristically.


### Phase 6: Final Review

Perform a final verification pass using concrete, checkable assertions before presenting results to the user.

**Check 1 — Entry count integrity**
- Count non-comment, non-blank data rows in the original input CSV.
- Assert: `len(entries) in report-data.json == data_row_count`
- On failure: `Row count mismatch: input has {N} data rows but report contains {M} entries.`

**Check 2 — Summary counter integrity**
- These counters use **mutual exclusion** based on the boolean flags, which mirrors the highest-severity `status` field. An entry with both `has_error: true` and `has_warning: true` is counted only in `error_count`, never in `warning_count`. This is equivalent to counting by the entry's `status` field.
- Assert all of the following; correct any that fail before generating the report:
  - `error_count == sum(1 for e in entries if e['has_error'])`
  - `warning_count == sum(1 for e in entries if e['has_warning'] and not e['has_error'])`
  - `suggestion_count == sum(1 for e in entries if e['has_suggestion'] and not e['has_error'] and not e['has_warning'])`
  - `ok_count == sum(1 for e in entries if not e['has_error'] and not e['has_warning'] and not e['has_suggestion'])`
  - `error_count + warning_count + suggestion_count + ok_count == total_entries - invalid_entries`

**Check 3 — Accuracy bucket integrity**
- Assert: `city_level_accuracy + region_level_accuracy + country_level_accuracy + do_not_geolocate_entries == total_entries - invalid_entries`
- **Note:** The accuracy buckets defined in Phase 3 say "Do not count entries with `has_error: true`", but the Check 3 formula above uses `total_entries - invalid_entries` (which still includes ERROR entries). This means ERROR entries (those that parsed as valid IPs but failed validation) **are** counted in accuracy buckets by their geo-field presence. Only `invalid_entries` (unparseable IP prefixes) are excluded. Follow the Check 3 formula as the authoritative rule.
- On failure, trace and fix the bucketing logic before proceeding.

**Check 4 — No duplicate line numbers**
- Assert: all `line` values in `entries` are unique.
- On failure, report the duplicated line numbers to the user.

**Check 5 — tuned_entries completeness**
- Assert: every object in `entries` has a `tuned_entries` key (even if its value is `[]`).
- On failure, add `"tuned_entries": []` to any entry missing the key, then re-save `report-data.json`.

**Check 6 — Report file is present and non-empty**
- Confirm `./run/report/geofeed-report.html` was written and has a file size greater than zero bytes.
- On failure, regenerate the report before presenting to the user.
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