Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cyanheads/congressgov-mcp-server --skill report-issue-localgit clone --depth 1 https://github.com/cyanheads/congressgov-mcp-serverWrote 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/cyanheads/congressgov-mcp-server/report-issue-local)<a href="https://agentmods.dev/skills/cyanheads/congressgov-mcp-server/report-issue-local"><img src="https://agentmods.dev/badge/skills/cyanheads/congressgov-mcp-server/report-issue-local/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/cyanheads/congressgov-mcp-server/report-issue-local"><img src="https://agentmods.dev/badge/skills/cyanheads/congressgov-mcp-server/report-issue-local.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 | $0.00044 | $0.03088 |
| Opus 5.5 | $0.00018 | $0.01235 |
| Sonnet 5.5 | $0.00009 | $0.00618 |
| Haiku 4.5 | $0.00004 | $0.00309 |
Grade A, and why
report-issue-local 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 28d 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.
This is a copy
100% identical to report-issue-local — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
The bug is in this server's code, not in @cyanheads/mcp-ts-core. Typical triggers:
- A tool handler returns wrong results or throws on valid input
- A service integration (external API, database, third-party SDK) fails or misbehaves
- Server-specific config (
server-config.ts) rejects valid env vars or has wrong defaults - Resource handlers return stale, incomplete, or incorrect data
- Domain logic errors — wrong calculations, missing edge cases, bad state transitions
- Missing or incorrect
.describe()on schema fields causing poor LLM tool use
If the issue is in the framework itself (builders, Context, utilities, type exports, linter), use report-issue-framework instead.
For general gh CLI workflows outside issue filing (PRs, workflows, API access), see the github-cli skill.
Before Filing
- Identify the repo:
gh repo view --json nameWithOwner -q '.nameWithOwner'
- Search existing issues — if a close match exists (same symptom, different tool; same tool, different symptom; closed issue that might cover the new case), add a comment on that issue instead of filing a new one — unless the symptom or scope is distinct enough to warrant separate tracking:
gh issue list --search "your error message or keyword" --state all
# Assess a close match before commenting — is it already linked to a fix or referenced elsewhere?
gh issue view <number> # body
gh issue view <number> --comments # thread only — without a TTY it prints no body
gh api 'repos/{owner}/{repo}/issues/<number>/timeline' --paginate \
--jq '.[] | select(.event=="cross-referenced") | .source.issue | "\(.repository.full_name)#\(.number) — \(.title)"'
-
Reproduce the issue — confirm it's reproducible. Note the exact input, transport mode, and any relevant env vars.
-
Check logs — review
ctx.logoutput and any framework telemetry for clues. If running HTTP, check the response body for structured error details.
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.
- 28d ago Changed · +2 lines eef9b7a4b5d6
- 1mo ago Changed · -26 lines d9b27bb4989c
- 1mo ago First seen · 310 lines · 44 tokens per session scan A 424389e230d2
report-issue-local is a skill published in the GitHub repository cyanheads/congressgov-mcp-server (1 stars, last pushed yesterday), licensed Apache-2.0. It adds 44 tokens to every session and 3,088 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to report-issue-local, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
report-issue
File a bug or feature request against this repository (cyanheads/git-mcp-server) using the gh CLI. Use for tool logic bugs, git provider misbehavior, transport issues, auth/config problems, or new feature proposals.
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quick-capture
Use this skill to drop a new task into GSD Task Manager from any AI assistant that has the gsd-mcp-server connected.
papi-idea
Invoke when submitting backlog ideas, registering docs, or filing research. Covers idea pipeline and doc registry conventions.
papi-integration-recipe
Use when the user wants to feed data from a connected MCP tool (Sentry, Linear, GitHub, Slack, or any other) into PAPI. Demonstrates the "host agent = integration bus" pattern: read from the external tool, map to PAPI shape, write via PAPI tool. PAPI never owns connectors — the user's AI session passes data between…