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Fact Checker

Name: Fact Checker
Author: nissan

by Nissan Dookeran · GitHub ↗ · v1.0.4 · MIT-0

cross-platform ✓ Security Clean

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Install in OpenClaw

/install fact-checker

Description

Verify claims, numbers, and facts in markdown drafts against source data. Use when: reviewing blog posts, reports, or documentation for accuracy before publi...

README (SKILL.md)

Last used: 2026-03-24 Memory references: 1 Status: Active

Fact-Checker: Verify Markdown Claims Against Source Data

Given a markdown draft file, this skill extracts every verifiable claim (numbers, dates, model names, scores, causal statements) and cross-references them against available source data to produce a verification report.

Usage

python3 skills/fact-checker/scripts/fact_check.py \x3Cdraft.md>
python3 skills/fact-checker/scripts/fact_check.py \x3Cdraft.md> --output report.md

What It Checks

Claim types extracted

Numeric claims — integers and floats with surrounding context
Model references — model/task (phi4/classify) and model:tag (phi4:latest)
Dates — YYYY-MM-DD format
Score values — decimal scores like 0.923, 1.000
Percentages — 42%, 95.3%

Source data consulted (in priority order)

projects/hybrid-control-plane/FINDINGS.md — primary source of truth
Control Plane /status API at http://localhost:8765/status — live scored run data
projects/hybrid-control-plane/data/scores/*.json — raw scored run files on disk
memory/*.md — daily logs with timestamps and decisions
git log in projects/hybrid-control-plane/ — commit hashes, dates, authorship
projects/hybrid-control-plane/CHANGELOG.md — sprint history

Output Format

Each claim produces one line:

✅ CONFIRMED:    "phi4/classify scored 1.000" → /status API: phi4_latest_classify mean=1.000 n=23
⚠️ UNVERIFIABLE: "this took about a day" → no timestamp correlation found in logs
❌ CONTRADICTED: "909 runs" → /status API shows 958 total runs (stale number?)

Followed by a summary count of confirmed / unverifiable / contradicted claims.

When To Use This Skill

When asked to "fact-check" or "verify" a draft blog post, report, or documentation file — run this skill and present the report to the user. If any claims are ❌ CONTRADICTED, flag them prominently and suggest corrections.

Instructions for Agent

Run the script with the path to the draft file.
Parse the output report.
Summarise key findings — especially any ❌ CONTRADICTED claims.
Suggest specific corrections with the correct values from the evidence.
If the /status API is unavailable, note it and rely on FINDINGS.md + score files.

Usage Guidance

This skill appears to do what it claims: it will read files under projects/hybrid-control-plane (FINDINGS.md, data/scores/*.json, CHANGELOG.md), memory/*.md, run git log in that project, and query a local service at http://localhost:8765/status. Before installing/use: (1) confirm you trust the local /status service and the project files it will read (they may contain sensitive data); (2) review the bundled scripts yourself (they are included) — the code is readable and only performs local reads, a git log, and a localhost HTTP GET; (3) be aware the script uses the requests library and a user-specific shebang path in the file header (non-portable but not harmful); (4) run the script on non-sensitive drafts or in an isolated environment if you are unsure. Minor notes: SKILL.md version (1.0.3) differs from registry version (1.0.4) and the script's shebang points to a local /Users/loki pyenv path — these are portability/information hygiene issues, not security blockers.

Capability Analysis

Type: OpenClaw Skill Name: fact-checker Version: 1.0.4 The fact-checker skill is a legitimate tool designed to verify numeric, date, and model-related claims in markdown documents against local project data (FINDINGS.md, CHANGELOG.md, git logs) and a local status API (localhost:8765). The Python script (fact_check.py) uses standard libraries and regex for extraction, and its subprocess usage is restricted to a hardcoded git command. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found.

Capability Assessment

✓ Purpose & Capability

The SKILL.md and scripts both state that verification comes from FINDINGS.md, local score JSON files, memory/*.md, git history under projects/hybrid-control-plane, and a localhost /status API. The code reads exactly those paths and calls http://localhost:8765/status and git log; these requirements match the stated purpose.

✓ Instruction Scope

Runtime instructions are narrow: run the bundled Python script on a draft file, parse its output, summarize contradictions, and suggest corrections. The script only reads local workspace files, score JSONs, memory logs, and runs a local git command. It does not attempt to read unrelated system config or request external endpoints.

✓ Install Mechanism

There is no install spec (instruction-only skill plus bundled scripts). The SKILL.md lists python3 as a required binary which is appropriate. Nothing is downloaded from the network or installed to disk by the skill itself.

✓ Credentials

The skill does not request environment variables or external credentials. It reads local project files and a localhost API which is proportionate to fact-checking claims against local test/run data. Note: those local files and memory logs may contain sensitive project information — access is justified for the skill's purpose but should be considered by the user.

✓ Persistence & Privilege

The skill does not request always:true or any elevated persistence. It runs as-needed and uses subprocess exec (git) and a local HTTP request; these are normal for this function.

How to Use

Make sure OpenClaw is installed (local or Docker)
Run the install command in chat: /install fact-checker
After installation, invoke the skill by name or use /fact-checker
Provide required inputs per the skill's parameter spec and get structured output

Version History

v1.0.4

Add security_notes: local-only verification, subprocess is bundled Python script

v1.0.3

Frontmatter fix: corrected malformed metadata block, added proper YAML network/subprocess flags

v1.0.2

Added complete frontmatter with security declarations

v1.0.1

Added metadata block with network disclosure (no outbound calls)

v1.0.0

- Initial release of the fact-checker skill. - Automatically identifies and cross-references numeric, model, date, score, and percentage claims in markdown drafts. - Verifies claims against FINDINGS.md, live API data, score files, memory logs, and git history. - Outputs a clear verification report categorizing claims as CONFIRMED, UNVERIFIABLE, or CONTRADICTED. - Summarizes results and flags contradicted claims with suggested corrections.

Metadata

Slug fact-checker

Version 1.0.4

License MIT-0

All-time Installs 14

Active Installs 13

Total Versions 5

Frequently Asked Questions

What is Fact Checker?

Verify claims, numbers, and facts in markdown drafts against source data. Use when: reviewing blog posts, reports, or documentation for accuracy before publi... It is an AI Agent Skill for Claude Code / OpenClaw, with 920 downloads so far.

How do I install Fact Checker?

Run "/install fact-checker" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Fact Checker free?

Yes, Fact Checker is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Fact Checker support?

Fact Checker is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Fact Checker?

It is built and maintained by Nissan Dookeran (@nissan); the current version is v1.0.4.

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