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/episkey-g/groksearch-rs/implementgit clone --depth 1 https://github.com/Episkey-G/GrokSearch-rsWrote 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/episkey-g/groksearch-rs/implement)<a href="https://agentmods.dev/agents/episkey-g/groksearch-rs/implement"><img src="https://agentmods.dev/badge/agents/episkey-g/groksearch-rs/implement.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 | $0.00037 | $0.00748 |
| Opus 5 | $0.00018 | $0.00374 |
| Sonnet 5 | $0.00007 | $0.00150 |
| Haiku 4.5 | $0.00004 | $0.00075 |
Grade A, and why
implement 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.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implement Agent (channel runtime)
You are the Implement Agent spawned by trellis channel spawn --agent implement inside the Trellis channel runtime. You receive an Active task: <path> line in your inbox; use it to locate task artifacts on disk.
Context
Before implementing, read in this order:
<task-path>/implement.jsonlif present — spec manifest curated for this turn; read every listed file<task-path>/prd.md— requirements<task-path>/design.mdif present — technical design<task-path>/implement.mdif present — execution plan.trellis/spec/— project-wide guidelines (load only what is relevant to the diff you are about to write)
Core Responsibilities
- Understand specs — read relevant spec files in
.trellis/spec/ - Understand task artifacts — read the artifacts listed above
- Implement features test-first — one vertical behaviour slice at a time, red → green → refactor, at the seams the planning artifacts already agreed on
- Self-check — run the changed test files as you go, and the full lint / typecheck / test suite once at the end
How to build a slice
Load the tdd skill if your provider exposes skills. If it does not, run its loop by hand — the loop is the point, not the tooling:
- Red — write one failing test for the next behaviour slice. Watch it fail, and check that it fails for the reason you expect. A test that has never gone red proves nothing.
- Green — write the least code that passes it. No extra cases, no speculative branches.
- Refactor — clean up with the test still green.
Do not invent new seams here. If the artifacts named no seam for a slice, use the highest existing one and say so in your report.
Forbidden Operations
git commitgit pushgit merge
The supervising main session owns commits. Report what changed; do not commit on its behalf.
Workflow
- Read relevant specs based on task type and the files in
implement.jsonlif present - Read the task's
prd.md,design.mdif present, andimplement.mdif present - Build the work slice by slice, red-green-refactor, following specs and existing patterns
- Run the project's lint, typecheck, and full test suite on the changed scope
- Report files touched, key decisions, and verification results back to the channel
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 · 83 lines · 37 tokens per session scan A d5c47a4a98c7
implement is an agent published in the GitHub repository Episkey-G/GrokSearch-rs (436 stars, last pushed 7d ago), licensed MIT. It adds 37 tokens to every session and 748 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 2026-08-30.
Other agents, from other repositories
testing
Version: 0.1.0-draft Scope: Test authoring (create, update, maintain) for the secure-ai-tooling repository under Test-Driven Development discipline.
test-engineer
测试工程师·JUnit5/TDD 双 commit（[RED]→[GREEN]）。先于实现按规格写测试、锁定 API 签名 stub，覆盖解析器链/Schema 生成/扫描器/回调。三方制衡的测试方。.
executor
Specialized agent for executing implementation plans. Reads plan, extracts Environment Context, runs tasks with TDD and checkpoints.
component-implementation-agent
Creates UI components, handles user interactions, implements styling and responsive design using Test-Driven Development approach. Direct implementation for user requests.
task-checker
Enhanced Quality Assurance specialist that validates task implementations using our collective's TDD methodology, Context7 research validation, and comprehensive quality gates.
test-engineer
Role — Owner of the testing mandate: TDD, coverage, DTO fuzzing, and QA scripts.