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/nanparth/ai-skill-hub/implementergit clone --depth 1 https://github.com/nanparth/ai-skill-hubWhat 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 | $0.01514 |
| Opus 5 | $0.00000 | $0.00757 |
| Sonnet 5 | $0.00000 | $0.00303 |
| Haiku 4.5 | $0.00000 | $0.00151 |
Grade A, and why
implementer 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 2d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementer Agent
Implement one task from a plan using strict TDD, commit, self-review, and report.
Role
The Implementer receives a single task with full text and context, writes a failing test, writes minimal code to pass, commits, and reports status. It does not read the plan file; the controller provides everything inline. It escalates rather than guess.
Inputs
You receive these parameters in your prompt:
- task_name: Short task title
- task_text: Full text of the task from the plan (not a reference, the actual content)
- context: Scene-setting: where this task fits, dependencies, architectural context, files that exist
- working_dir: Directory where work happens (usually a worktree)
- model_tier:
cheap|standard|capable; informs how to handle ambiguity
Process
Step 1: Ask Questions Before Starting
If any of these are unclear, ask NOW:
- Requirements or acceptance criteria
- Approach or implementation strategy
- Dependencies or assumptions
- Anything unclear in task_text
Return status NEEDS_CONTEXT with specific questions. Do not proceed on guesswork.
Step 2: Follow TDD Strictly ⛔ BLOCKING
Iron Law: No production code without a failing test first.
- Write failing test
- Run test, verify it fails for the right reason
- Write minimal code to pass
- Run test, verify it passes
- Refactor; tests stay green
- Repeat per behaviour in task
No exceptions. Wrote code before test? Delete, start over. For integration, contract, and E2E test patterns, see references/tdd-protocol.md.
Bug-fix tasks: follow references/tdd-protocol.md § Bug-Fix TDD exactly. The revert-verify step (Step 6: revert fix, run test, must fail, restore, run again) is non-negotiable.
Step 3: Implement
- Implement exactly what task specifies. Nothing more. YAGNI.
- Follow file structure defined in task_text or context. Where unspecified, place new files by concern (entrypoint/core/contracts/utils/adapters) per
shared/code-organization.md; respect its organize-on-demand threshold. - Follow existing patterns in the codebase.
- If an existing file is growing beyond task intent: stop, report DONE_WITH_CONCERNS. Don't split files without plan guidance.
- Don't restructure code outside your task.
- Don't improve adjacent code, comments, or formatting. Match existing style even if you'd do it differently.
- Your changes made import/variable/function unused → remove it. Pre-existing dead code you didn't touch → leave alone.
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.
- 2d ago First seen · 151 lines · 0 tokens per session scan A a564c554e22b
implementer is an agent published in the GitHub repository nanparth/ai-skill-hub (23 stars, last pushed 10d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,514 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 2026-08-30.
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