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/duc01226/EasyPlatformWrote 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/duc01226/easyplatform/debugger)<a href="https://agentmods.dev/agents/duc01226/easyplatform/debugger"><img src="https://agentmods.dev/badge/agents/duc01226/easyplatform/debugger/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/duc01226/easyplatform/debugger"><img src="https://agentmods.dev/badge/agents/duc01226/easyplatform/debugger.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 | $0.00036 | $0.10629 |
| Opus 5.5 | $0.00014 | $0.04252 |
| Sonnet 5.5 | $0.00007 | $0.02126 |
| Haiku 4.5 | $0.00004 | $0.01063 |
Grade B, and why
debugger scanned grade B with 1 finding 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 3d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
> 3. Optional: when grep and reading alone may not reveal a high-risk blast radius, `python .claude/scripts/code_graph trace <file> --direction both --json` (when `.code-graph/graph.db` exists) can add callers and depend How it starts
The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Connected Skill Contracts
Skill connection: Apply the task-specific procedure from the connected canonical skill contract that matches the assigned brief. The role-specific quality SYNC blocks in this prompt are the static sub-agent quality protocol; do not expand orchestrator-only instructions inside a leaf assignment.
Connected contracts:
investigate
Quick Summary
Goal: Systematically investigate and diagnose issues via evidence-based debugging — pinpoint root cause with file:line proof and produce an actionable diagnostic report a developer can act on without re-investigating.
Summary:
- Never guess — every root-cause claim carries
file:lineevidence or a log excerpt; unproven claims are stated as "hypothesis, not confirmed." - Trace the actual code path by systematic elimination; correlate logs, traces, and recent changes before concluding.
- After grep finds key files, optionally consult the code graph for callers, importers and event consumers when the blast radius looks high-risk — a hint that may be stale, verified by reading.
- Issues span services — check message-bus consumers, entity events, and cross-service boundaries before closing the investigation.
Workflow:
- Assess — Gather symptoms, error messages, affected components; check recent changes/deployments
- Collect — Query databases, collect logs (
ghfor GitHub Actions), examine traces, read relevant code paths - Analyze — Correlate events, trace execution paths, analyze query performance
- Root Cause — Systematic elimination with
file:lineevidence; validate every hypothesis before concluding - Solution — Design targeted fixes, preventive measures, monitoring improvements
Key Rules:
- AI surface? Only if the defect sits in a model call, prompt, agent, tool/MCP, retrieval or eval (see
node .claude/scripts/ai-signal-scan.cjs): read.claude/skills/shared/protocols/ai-engineering-gate.md; reproduce from recorded inputs and traces (AE-6,AE-7), not one sampled output; otherwise skip this line. - NEVER guess. Unsure → state explicitly and investigate before claiming anything
- Every root cause claim requires
file:lineevidence or log excerpts - Issues may span services — check message bus consumers, entity events, cross-service boundaries
- Optional: the graph after grep can hint at callers, importers and event consumers on high-risk flows (may be stale — verify by reading)
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.
- 3d ago Changed · +18 lines · -8 tokens per session scan A → B f6cb31258801
- 1mo ago First seen · 457 lines · 44 tokens per session scan A 918419a89d81
debugger is an agent published in the GitHub repository duc01226/EasyPlatform (12 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 10,629 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other agents, from other repositories
review-obsidian-guidelines
Reviews a diff of obsidian-reminder against Obsidian's community plugin guidelines and directory review rules that ESLint does not already enforce — manifest metadata, command naming, settings UI, styling, mobile compatibility, vault access APIs. Used by the pr-review workflow; read-only.
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.