Borrowing it
Nothing to install: this file belongs to davesheffer/hunch. 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/davesheffer/hunch/main/.agents/skills/source-command-hunch-fragile/SKILL.mdgit clone --depth 1 https://github.com/davesheffer/hunchWrote 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/davesheffer/hunch/source-command-hunch-fragile)<a href="https://agentmods.dev/skills/davesheffer/hunch/source-command-hunch-fragile"><img src="https://agentmods.dev/badge/skills/davesheffer/hunch/source-command-hunch-fragile.svg" alt="Measured on agentmods" 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 | $0.00020 | $0.00130 |
| Opus 5 | $0.00010 | $0.00065 |
| Sonnet 5 | $0.00004 | $0.00026 |
| Haiku 4.5 | $0.00002 | $0.00013 |
Grade A, and why
source-command-hunch-fragile 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 7d 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.
What it actually says
source-command-hunch-fragile
Use this skill when the user asks to run the migrated source command hunch-fragile.
Command Template
Ask Hunch for the fragility ranking (run hunch fragile or query Hunch),
then produce a fragility report with evidence: the specific files/functions,
the bug history behind them, their churn and fan-in, and any missing guards.
Avoid generic advice — every claim must cite a Hunch record or metric.
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.
- 7d ago First seen · 16 lines · 20 tokens per session scan A e2cf66a9755c
source-command-hunch-fragile is a skill published in the GitHub repository davesheffer/hunch (9 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 130 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
changes-report
Report all repository changes that entered a target branch during one required date or period, grouped by product change and written as plain English for a broad audience. Use for daily, weekly, date-range, or relative-period change summaries rather than explaining one known diff.
jira-issue-create
Create one or more Jira issues through acli from user-approved drafts using heading-based Context, Acceptance criteria, and Engineering notes sections. Use only when explicitly invoked to create Jira issues; use jira-issue-refine when requirements still need refinement.
claude-review
Run an independent Claude Opus review of the complete current change against the repository's default branch, then verify its findings locally. Use after focused checks pass when you want a second model to review the change before further edits or delivery.
test-gap-review
Review whether existing tests and verification credibly prove a scoped behavior contract. Use during validation when evidence may omit important behavior or provide false confidence.
jira-issue-deliver
Autonomously deliver one Jira issue from intake to a ready GitHub pull request. Use only when the user authorizes implementation, commits, pushes, PR state changes, CI remediation, and resolution of requested automated review feedback.
change-cleanup-review
Review a complete change for unwanted scope, redundant or residual artifacts, review-obscuring churn or prose, hollow verification, and work shifted to reviewers. Use before human review and after review-driven fixes, not for general implementation review or AI-authorship inference.