Borrowing it
Nothing to install: this file belongs to amkessler/nicar2026_skills_in_codex_claude. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/amkessler/nicar2026_skills_in_codex_claude/main/.claude/skills/fecfile/SKILL.mdgit clone --depth 1 https://github.com/amkessler/nicar2026_skills_in_codex_claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/amkessler/nicar2026_skills_in_codex_claude/fecfile)<a href="https://agentmods.dev/skills/amkessler/nicar2026_skills_in_codex_claude/fecfile"><img src="https://agentmods.dev/badge/skills/amkessler/nicar2026_skills_in_codex_claude/fecfile/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/amkessler/nicar2026_skills_in_codex_claude/fecfile"><img src="https://agentmods.dev/badge/skills/amkessler/nicar2026_skills_in_codex_claude/fecfile.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.02398 |
| Opus 5 | $0.00020 | $0.01199 |
| Sonnet 5 | $0.00008 | $0.00480 |
| Haiku 4.5 | $0.00004 | $0.00240 |
Grade A, and why
fecfile scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FEC Filing Analysis
This skill enables analysis of Federal Election Commission campaign finance filings.
Requirements
- uv must be installed
- Python 3.9+
Dependencies are automatically installed when running the script with uv run.
First-Time Check
The first time this skill is invoked in a session, verify that uv is installed by running:
uv --version
If this command fails or uv is not found, do not proceed. Instead, inform the user that uv is required but not installed, and direct them to the installation guide: https://docs.astral.sh/uv/getting-started/installation/
Quick Start
Always start by checking the filing size:
uv run --script skills/fecfile/scripts/fetch_filing.py <FILING_ID> --summary-only
Based on the summary, decide how to proceed—see Handling Large Filings below for filtering and streaming strategies. Small filings can be fetched directly; large filings require pre-filtering or streaming.
Fetching data:
uv run --script skills/fecfile/scripts/fetch_filing.py <FILING_ID> # Full filing (small filings only)
uv run --script skills/fecfile/scripts/fetch_filing.py <FILING_ID> --schedule A # Only contributions
uv run --script skills/fecfile/scripts/fetch_filing.py <FILING_ID> --schedule B # Only disbursements
uv run --script skills/fecfile/scripts/fetch_filing.py <FILING_ID> --schedules A,B # Multiple schedules
The fecfile library is installed automatically by uv.
Field Name Policy
IMPORTANT: Do not guess at field names. Before referencing any field names in responses:
- For form-level fields (summary data, cash flow, totals): Read
references/FORMS.md - For itemization fields (contributors, payees, expenditures): Read
references/SCHEDULES.md
These files contain the authoritative field mappings. If a field name isn't documented there, verify it exists in the actual JSON output before using it.
Handling Large Filings
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 257 lines · 41 tokens per session scan A 9d8116e92400
fecfile is a skill published in the GitHub repository amkessler/nicar2026_skills_in_codex_claude (20 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 41 tokens to every session and 2,398 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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