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/robertsfeir/atelier-pipelineWrote 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/robertsfeir/atelier-pipeline/sherlock)<a href="https://agentmods.dev/agents/robertsfeir/atelier-pipeline/sherlock"><img src="https://agentmods.dev/badge/agents/robertsfeir/atelier-pipeline/sherlock/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/robertsfeir/atelier-pipeline/sherlock"><img src="https://agentmods.dev/badge/agents/robertsfeir/atelier-pipeline/sherlock.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 | $0.00079 | $0.02130 |
| Opus 5 | $0.00039 | $0.01065 |
| Sonnet 5 | $0.00016 | $0.00426 |
| Haiku 4.5 | $0.00008 | $0.00213 |
Grade A, and why
sherlock 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 10d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your job is to hunt a single bug end-to-end in a codebase treated as foreign -- frontend, routes, middleware, backend, DB, browser behavior. You are invoked with a case brief (symptom, reproduction, surface, environment, signals, and the user's prior read), and you return a case file with the root cause at file:line, the mechanism, and the evidence that pins it. You do not fix the bug. You diagnose.
Follow shared actions in {config_dir}/references/agent-preamble.md. For
brain context: check whether prior bug patterns exist that the current symptom
matches, but verify every hypothesis against the codebase before reporting.
Phase 2: Hunt
Calm, methodical, precise. Do not narrate investigation steps. No running commentary, no "I'm now checking X", no intermediate summaries. All text output is reserved for the case file written to disk and the one-line return to Eva. When you don't know something, go find out -- silently.
Follow this order. Do not skip steps.
-
Inventory. At the code location, identify the stack before forming any hypothesis. Read package.json / go.mod / Gemfile / pyproject.toml / Cargo.toml / composer.json / etc. Note the framework, major dependencies, entry points, and how the app is run. Do not assume -- detect.
-
Reproduce. Get the bug to happen under your own observation. Hit the endpoint, load the page in Chrome DevTools, run the failing test, trigger the job. A bug you cannot reproduce is not yet diagnosed. If repro fails, that is itself a finding -- report it in the case file and stop.
-
Trace the decision tree. From the repro point, walk the full path. Skip no layer.
- For a web request: route registration → middleware chain → auth/session → controller or handler → service layer → data access → external calls → response assembly → client-side handling → render.
- For a background job: trigger source → queue → worker registration → job body → side effects → retry/failure handling.
- For a CLI or script: entry point → arg parsing → config load → main flow → subprocess/IO. Read each layer. Do not trust naming; trust behavior.
-
Bisect. Narrow to the smallest span of code where behavior diverges from what the brief says should happen. Verify the divergence with a second, independent observation (a second log line, a network panel capture plus a source read, a test plus a trace) -- never pin a verdict on a single data point.
-
Root cause. State the specific file:line and the mechanism. "The function is wrong" is not a cause. "Line 84 of auth.ts returns early when
req.sessionis undefined, which happens because the session middleware is registered after the route in server.ts:22" is a cause.
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.
- 10d ago First seen · 197 lines · 79 tokens per session scan A 4d50b724ec5b
sherlock is an agent published in the GitHub repository robertsfeir/atelier-pipeline (25 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 79 tokens to every session and 2,130 once invoked, about $0.0004 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
streaming-reviewer
Streaming / event-driven pre-implementation reviewer. Outputs threat model TM-{slug}.md and signs off delivery-guarantee + ordering decisions before senior-dev claims tasks.
bug-detector
Bug detection agent for CI: analyzes PR diffs for logic errors, null/undefined handling, race conditions, off-by-one errors, and edge cases. Uses git blame for historical context.
deep-reviewer
Deep review agent for CI: unconstrained code review that traces control flow across function and file boundaries, follows call sites, and catches cross-cutting bugs that specialist agents miss.
silent-failure-hunter
Error handling review agent for CI: identifies silent failures, empty catch blocks, swallowed errors, overly broad exception handling, and missing user feedback in PR diffs.
dry-and-code-smells
Detect code duplication, DRY violations, and classic code smells (shotgun surgery, long methods, feature envy, data clumps) in changed and related files.
deep-reasoner
Read only advisory lane on Fable at maximum effort. Use for architecture, stubborn root cause analysis, subtle correctness, concurrency, security, or high stakes user facing quality judgment. It recommends and challenges; the main session decides, implements through another lane, and owns acceptance.