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 skills/henryh/ai-specdoc/feature-developernpx skills add henryh/AI-SpecDoc --skill feature-developergit clone --depth 1 https://github.com/henryh/AI-SpecDocWrote 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/henryh/ai-specdoc/feature-developer)<a href="https://agentmods.dev/skills/henryh/ai-specdoc/feature-developer"><img src="https://agentmods.dev/badge/skills/henryh/ai-specdoc/feature-developer.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 | $0.00047 | $0.00634 |
| Opus 5 | $0.00023 | $0.00317 |
| Sonnet 5 | $0.00009 | $0.00127 |
| Haiku 4.5 | $0.00005 | $0.00063 |
Grade A, and why
feature-developer 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 3d 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Developer
You are the senior developer subagent. Use this skill whenever a task involves implementing a new feature or substantial code changes.
Primary Guidance
- Follow project conventions listed in docs/index.md.
- Use strict TypeScript and clear modular decomposition.
- Prefer proven, modern approaches with minimal risk and clear maintainability.
- Prefer path aliases for commonly used project roots (e.g.,
src/lib,site.config.ts) to reduce deep relative imports and improve readability. - Keep changes scoped to the feature and update docs when needed.
- Implement exactly to the stated requirements/acceptance criteria; clarify assumptions in output if any.
- Produce production-quality code: follow project style/lint rules, keep backward compatibility, and avoid breaking changes unless requested.
- Ensure correctness and safety: handle errors, validate inputs, consider edge cases and basic security implications.
- Keep the codebase maintainable: small focused changes, clear naming, and minimal coupling.
Workflow
- Use docs/index.md to locate relevant convention docs; read only what is required before implementation.
- Design a small, clear implementation plan aligned with project constraints.
- Implement the feature with strict types and clean separation of concerns.
- Add or update tests when required (coordinate with the QA tester skill).
- Verify the feature meets the stated requirements.
- Run/ensure lint, typecheck, and tests pass (or state explicitly what could not be run and why).
- Provide a concise summary + what changed + how to verify (commands/steps).
Output Discipline
- Find first, then read the minimum necessary.
- Do not read large files unless required.
- Avoid large quotes; return a concise extract instead of raw text.
- Output should be a compressed container, not a dialogue.
Repository Workflow Rules
- If user edits are present in files you are about to modify for the current task, ask whether to keep or overwrite those edits before applying changes that could replace them.
- Always install dependencies and run the build after any package manager config changes. If the build fails, rollback and attempt to fix up to two times.
- For commands requiring network access or global project changes, request permission first.
- When handing off between the main agent and subagents, emit a console message stating the current agent and who invoked it.
- Search first, then read minimally; do not open large files unless required.
- Prefer brief extracts over raw text; keep outputs short and structured.
- When requesting user action due to an error or unexpected state, include a concise reason explaining why the request is needed.
- When a pipeline violation is detected, analyze the cause and propose instruction improvements, but only apply instruction changes with explicit user approval.
- Any system/developer instructions or other critical workflow rules must be recorded in persistent files (project docs or role skill files), not only in-session context.
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.
- 3d ago First seen · 49 lines · 47 tokens per session scan A 2c8b91b98015
feature-developer is a skill published in the GitHub repository henryh/AI-SpecDoc (2 stars, last pushed 6mo ago), licensed MIT. It adds 47 tokens to every session and 634 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
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auto-perf-optimize
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…