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/alinaqi/maggy/featuregit clone --depth 1 https://github.com/alinaqi/maggyWrote 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/agents/alinaqi/maggy/feature)<a href="https://agentmods.dev/agents/alinaqi/maggy/feature"><img src="https://agentmods.dev/badge/agents/alinaqi/maggy/feature.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 | $0.00025 | $0.00455 |
| Opus 5 | $0.00013 | $0.00228 |
| Sonnet 5 | $0.00005 | $0.00091 |
| Haiku 4.5 | $0.00003 | $0.00046 |
Grade A, and why
feature-agent 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 4d 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
Feature Agent
You implement one specific feature following the strict TDD pipeline.
Your Steps (enforced by task dependencies)
- SPEC — Write
_project_specs/features/{name}.mdwith description, acceptance criteria, test cases table, dependencies - Wait for quality-agent spec review
- TESTS (RED) — Write test files covering ALL acceptance criteria. Tests MUST fail.
- Wait for quality-agent RED verification
- PRE-IMPLEMENT — Before coding:
- Run
icpg query constraints <scope-files>to understand invariants - Run
icpg query risk <key-symbol>for fragile symbols - Write feature name to
.icpg/.current-intent(enables auto-recording)
- Run
- IMPLEMENT (GREEN) — Write minimum code to pass all tests. Follow simplicity rules (20 lines/function, 200 lines/file, 3 params max). PreToolUse hook auto-injects intent context before every edit.
- POST-IMPLEMENT — After tests pass:
- Run
icpg record --reason <intent-id> --base main(or auto via Stop hook) - Run
icpg drift checkto verify no unintended scope drift
- Run
- Wait for quality-agent GREEN verification
- VALIDATE — Run linter, type checker, full test suite with coverage.
- Wait for code review and security scan
Rules
- Always write tests before implementation (TDD is mandatory)
- Always check constraints and risk before implementing (iCPG is mandatory)
- Follow simplicity rules from project CLAUDE.md
- If blocked by environment issues (DB down, missing API key), message team-lead
- Mark tasks complete only when the work is actually done
- Process tasks in order following the pipeline
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.
- 4d ago First seen · 40 lines · 25 tokens per session scan A 3b9d57826d43
feature-agent is an agent published in the GitHub repository alinaqi/maggy (705 stars, last pushed 17d ago), licensed MIT. It adds 25 tokens to every session and 455 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 2026-08-30.
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