Borrowing it
Nothing to install: this file belongs to damian-demasi-aligent/ai-agent-tool-chain-generic. 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/damian-demasi-aligent/ai-agent-tool-chain-generic/main/.claude/skills/implement-feature/SKILL.mdgit clone --depth 1 https://github.com/damian-demasi-aligent/ai-agent-tool-chain-genericWrote 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/damian-demasi-aligent/ai-agent-tool-chain-generic/implement-feature)<a href="https://agentmods.dev/skills/damian-demasi-aligent/ai-agent-tool-chain-generic/implement-feature"><img src="https://agentmods.dev/badge/skills/damian-demasi-aligent/ai-agent-tool-chain-generic/implement-feature/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/damian-demasi-aligent/ai-agent-tool-chain-generic/implement-feature"><img src="https://agentmods.dev/badge/skills/damian-demasi-aligent/ai-agent-tool-chain-generic/implement-feature.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 | $0.00049 | $0.01987 |
| Opus 5 | $0.00024 | $0.00993 |
| Sonnet 5 | $0.00010 | $0.00397 |
| Haiku 4.5 | $0.00005 | $0.00199 |
Grade A, and why
implement-feature scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Run a dev server smoke test (start the dev server, curl the app AND a data-fetching route, check for runtime and backend connectivity errors) — this catches provider ordering bugs, server/client boundary mistakes, miss The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 12d ago First seen · 187 lines · 49 tokens per session scan A 6bf801beebad
implement-feature is a skill published in the GitHub repository damian-demasi-aligent/ai-agent-tool-chain-generic (2 stars, last pushed 5mo ago), with no licence file. It adds 49 tokens to every session and 1,987 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or…