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 agentmods add agents/mdelapenya/coding-skills/genericgit clone --depth 1 https://github.com/mdelapenya/coding-skillsWhat 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 | $0.00000 | $0.00438 |
| Opus 5 | $0.00000 | $0.00219 |
| Sonnet 5 | $0.00000 | $0.00088 |
| Haiku 4.5 | $0.00000 | $0.00044 |
Grade A, and why
generic 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 yesterday.
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
Generic / Unknown Agent
Fallback topic file for any agent that does not have a dedicated entry under references/agents/.
Fetch tooling
The skill drives its own fetch. If the agent has shell access, gh (GitHub) and glab (GitLab) are the canonical tools. If the agent only has an MCP server for the host (e.g., GitHub MCP), use that for metadata/diff/issues — but git clone for Step 2c of the skill still requires shell access. If the agent has neither shell nor a relevant MCP, the user must check out the PR before invoking; the skill cannot manufacture data.
Looping primitive
Most coding agents do not have a built-in loop primitive today (Claude Code is the exception — see claude.md). For everything else, pick the most automation-friendly option your agent supports, in increasing order of automation:
- Manual — the user re-invokes
/pr-reviewer [<num>]after each round until the skill reports convergence or--rounds=Nis hit. - Agent task description — tell the agent in plain language: "Run
/pr-reviewer [<num>]up to 3 times, stopping early onconverged: true." Multi-step agents will sequence this correctly. - External shell driver — drive the agent from a shell
for/whilethat breaks on the convergence marker:for i in $(seq 1 3); do <agent-invocation-here> "/pr-reviewer [<num>]" grep -q '^- converged: true$' "<base-dir>/findings.md" && break done
--rounds=N is the universal hard stop. Always pass it.
Posting the final report
The skill prints the report by default. If the agent has the ability to post to the source platform, confirm with the user first, then use whichever tool the agent provides. Otherwise print the report and let the user post it manually.
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.
- yesterday First seen · 28 lines · 0 tokens per session scan A 3769a5933bb0
generic is an agent published in the GitHub repository mdelapenya/coding-skills (2 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 438 tokens. 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.
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