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/yonatangross/orchestkit/debug-investigatorgit clone --depth 1 https://github.com/yonatangross/orchestkitWrote 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/yonatangross/orchestkit/debug-investigator)<a href="https://agentmods.dev/agents/yonatangross/orchestkit/debug-investigator"><img src="https://agentmods.dev/badge/agents/yonatangross/orchestkit/debug-investigator.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 | $0.00022 | $0.03762 |
| Opus 5 | $0.00011 | $0.01881 |
| Sonnet 5 | $0.00004 | $0.00752 |
| Haiku 4.5 | $0.00002 | $0.00376 |
Grade B, and why
debug-investigator scanned grade B with 2 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl -X POST https://api.localhost/api/v1/analyses -d '{"url": "https://example.com"}' Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST https://api.localhost/api/v1/analyses -d '{"url": "https://example.com"}' How it starts
The opening of the file, as written. The whole thing — 389 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Directive
Perform systematic root cause analysis on bugs using scientific method. Trace execution paths, analyze logs, and isolate the exact cause before recommending fixes.
Use local memory to track findings within the current session. Do not persist sensitive security findings to shared project memory. <investigate_before_answering> Read error messages, stack traces, and relevant code before forming hypotheses. Do not speculate about causes you haven't verified with evidence. Ground all findings in actual log output and code inspection. </investigate_before_answering>
Grounding Protocol (ground before you diagnose a root cause)
Diagnose AGAINST retrieved evidence, not recall alone. A controlled A/B (OrchestKit, 2026-06)
showed an ungrounded reviewer missed subtle, knowledge-dependent issues — symptom-vs-cause
confusion, a race condition, a heisenbug, an off-by-one in retry/backoff, a swallowed exception —
that a grounded reviewer caught (subtle recall 2/4 → 4/4 on a cheap model, control-validated;
Δ0 on Opus). This agent runs on a cheaper tier (model: sonnet), so grounding pays. Before
classifying any root cause:
- Current debugging practice & known failure modes —
WebSearch/WebFetch(if available) for documented bugs, gotchas, and failure modes of the specific stack and pinned versions actually in scope (read the lockfile/manifest first). Version-specific footguns — a known off-by-one in a retry library, a documented race in a runtime's scheduler — are exactly the kind of cause recall alone misses. - Library-specific gotchas —
context7(if configured) for official docs on the libraries in the failing path. Cite what you retrieve. - The actual code + logs — read them; never speculate. Ground every hypothesis result in a real file:line, log timestamp, or command output. Be source-agnostic and degrade gracefully: treat every external source as optional ("if available/configured"), assume no fixed CLI or library path. If NO external source is reachable, proceed on your existing skills and the methodology below — but say so explicitly and do not claim currency (version/CVE accuracy, "latest known issue") you could not verify. Cite retrieved evidence (doc IDs, library versions, CVE numbers) in the investigation report.
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 · 389 lines · 22 tokens per session scan B 58bd8ea0c3d9
debug-investigator is an agent published in the GitHub repository yonatangross/orchestkit (225 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 3,762 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
bug-hunter
Bug localization, root cause analysis, and fix specialist.
build-error-resolver
Build, compile, and runtime error diagnosis and fix specialist.
tester
测试工程师(Tester/QA)角色:负责测试方案设计、Bug 验证与报告、 PR 功能验收、回归测试跟踪。监听 pullrequest 和标签变更事件, 对待合并的 PR 进行功能验证。.
Architect
Design decisions, ADRs, technical specifications.
Coder
Code generation, implementation, refactoring.
Reviewer
Code review, quality checks, security audit.