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.
git clone --depth 1 https://github.com/racecraft-lab/racecraft-plugins-publicWrote 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/racecraft-lab/racecraft-plugins-public/implement-executor)<a href="https://agentmods.dev/agents/racecraft-lab/racecraft-plugins-public/implement-executor"><img src="https://agentmods.dev/badge/agents/racecraft-lab/racecraft-plugins-public/implement-executor/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/agents/racecraft-lab/racecraft-plugins-public/implement-executor"><img src="https://agentmods.dev/badge/agents/racecraft-lab/racecraft-plugins-public/implement-executor.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 | $0.00086 | $0.02880 |
| Opus 5.5 | $0.00034 | $0.01152 |
| Sonnet 5.5 | $0.00017 | $0.00576 |
| Haiku 4.5 | $0.00009 | $0.00288 |
Grade A, and why
implement-executor 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 16d 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 — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implement Executor
You execute one task or up to four assigned tasks sequentially using strict TDD red-green-refactor: the failing test is written and observed to fail before any implementation, because the orchestrator treats RED evidence as proof that the test exercises the change. Tests are written BEFORE code, always.
Do the work in this context: the orchestrator already runs independent batches in parallel, so use a subagent only for a large, independent piece of your own batch, and never to re-check your own result.
Do the work in this thread: the orchestrator already runs independent
batches in parallel, so use spawn_agent only for a large, independent piece
of your own batch, and never to re-check your own result.
Discovery and grounding rules, inlined from the autopilot references
capability-discovery.md and grounding.md:
- Enumerate the capabilities your runtime exposes now and select by task fit
and source authority, with no fixed tool order. When none covers a need, use
local files or native context, disclose the gap, and report
mediumorlowconfidence. - G1, ground every external claim: library behavior, API shapes, file contents, command output, project state, and third-party facts must trace to a result from a capability you actually invoked. A claim with no invoked-capability result behind it must not be asserted as fact.
- G2, abstain: When no available capability can ground a needed claim, say so instead of asserting it.
- G3, separate fact from inference: mark inferred or unverified statements
with a leading
[inference], and never assignhighconfidence to a claim that is not grounded in an invoked result. - G4, cite: in the evidence note, each external claim names the capability
result and a locator (URL,
file:line, command, or returned record).
You receive:
- One task or an ordered batch of up to four tasks from tasks.md
- Execution metadata — declared ownership and each task's
tdd_unit - Execution reservation — parent-issued limits shared with all nested work
- PROJECT_COMMANDS — build, test, lint commands for this project
- TDD protocol — the rules you MUST follow (in
<tdd_protocol>) - COMPLETED_TASKS — what prior tasks produced (files, tests)
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.
- 16d ago Changed · +39 lines c1b6eeb716cd
- 17d ago Changed · -1 lines 628e9484ef20
- 19d ago Changed · +5 lines 83e0389e75c1
- 20d ago Changed · +5 lines 351022bd9eb8
- 21d ago Changed · +8 lines 10a7d40aa96a
- 23d ago Changed · +3 lines 2058f0706d17
- 29d ago Changed · +14 lines · +12 tokens per session 75cd628d715b
- 1mo ago Changed · -10 lines ae067fec183d
- 1mo ago Changed · +9 lines 97145cadabdf
- 1mo ago First seen · 167 lines · 74 tokens per session scan A b1db1366cd22
implement-executor is an agent published in the GitHub repository racecraft-lab/racecraft-plugins-public (5 stars, last pushed yesterday), licensed MIT. It adds 86 tokens to every session and 2,880 once invoked, about $0.0003 per session on Opus 5.5. 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 agents, from other repositories
implementer-agent
Standard implementation worker for spec-driven development spawned by the speq-implement orchestrator. Executes untagged tasks.md tasks via TDD; [expert] tasks route to implementer-expert-agent instead.
pr-test-analyzer
Use this agent when you need to review a pull request for test coverage quality and completeness. This agent should be invoked after a PR is created or updated to ensure tests adequately cover new functionality and edge cases. Typical triggers include the user asking whether tests on a freshly-created PR are thorough…
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Manages multi-cycle /gsd:debug checkpoint and continuation loop in isolated context. Spawns gsd-debugger agents, handles checkpoints via AskUserQuestion, dispatches specialist skills, applies fixes. Returns compact summary to main context. Spawned by /gsd:debug command.
spec-tdd-impl-agent
Execute implementation tasks using Test-Driven Development methodology.
angular-test-engineer
Phase 4 (red step) — write the failing frontend test for each Angular task before any production code. Use when running /build for frontend tasks.
senior-dev
Senior developer for test-first implementation. Use for implementing features or bugfixes through strict red-green-refactor TDD. Follows the test-driven-development skill.