Borrowing it
Nothing to install: this file belongs to jeffrey2423/commit-like-pro. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jeffrey2423/commit-like-pro/main/.claude/skills/bmad-investigate/SKILL.mdgit clone --depth 1 https://github.com/jeffrey2423/commit-like-proWrote 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/skills/jeffrey2423/commit-like-pro/bmad-investigate)<a href="https://agentmods.dev/skills/jeffrey2423/commit-like-pro/bmad-investigate"><img src="https://agentmods.dev/badge/skills/jeffrey2423/commit-like-pro/bmad-investigate.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 5.1 | $0.00055 | $0.02504 |
| Opus 5 | $0.00028 | $0.01252 |
| Sonnet 5 | $0.00011 | $0.00501 |
| Haiku 4.5 | $0.00006 | $0.00250 |
Grade A, and why
bmad-investigate 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 7d 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.
This is a copy
100% identical to bmad-investigate — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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.
Investigate
Overview
Reconstruct what's happening, or what an unfamiliar area does, from the available evidence. Produce a structured case file another engineer can pick up cold. Calibrate continuously between defect-chasing (symptom-driven) and area-exploration (no symptom); the same discipline applies on both ends.
Args: A ticket ID, log file path, diagnostic archive, error message, code area name, problem description, or a path to an existing case file. The last form resumes a prior investigation; everything else opens a new case.
Output: {implementation_artifacts}/{workflow.case_file_subdir}/{workflow.case_file_filename}. Reference inputs
are recorded; raw content is not read into the parent context until an outcome calls for it.
{slug} is the ticket ID when one is provided, otherwise a short descriptive name agreed with the user, sanitized to
lowercase alphanumeric with hyphens. On collision with an existing case file at the resolved path, ask whether to
rename to slug-YYYY-MM-DD.md or resume the existing file (resuming routes to Outcome 0).
After every outcome, present what was learned and pause for the user before continuing.
Principles
- Evidence grading.
- Confirmed. Directly observed; cite
path:line, log timestamp, or commit hash. - Deduced. Logically follows from Confirmed evidence; show the chain.
- Hypothesized. Plausible but unconfirmed; state what would confirm or refute it.
- Confirmed. Directly observed; cite
- Stronghold first. Anchor in one Confirmed piece of evidence and expand outward. Never start from a theory and hunt for support. When evidence is sparse, switch to evidence-light mode (Outcome 1 branch).
- Challenge the premise. The user's description is a hypothesis, not a fact. Verify independently; if evidence contradicts, say so.
- Follow the evidence, not the narrative. When evidence contradicts the working theory, update the theory — never the other way around. Resist confirmation bias even when the user is convinced.
- Hypotheses are never deleted. Update Status (Open / Confirmed / Refuted) and add a Resolution. Wrong turns are part of the deliverable.
- Missing evidence is itself a finding. Document the gap, what it would resolve, and how to obtain it.
- Write it down early. Initialize the case file as soon as the slug is agreed; it is the persistent state across interruptions.
- Path:line citations use CWD-relative format, no leading
/, so they're clickable in IDE-embedded terminals. - Delegation discipline. When a step requires reading 5+ files or any file >10K tokens, delegate to a subagent
that returns structured JSON only. Cite
path:linefrom the result; don't re-read in the parent. - Issue independent operations in parallel (multi-grep, multi-read, parallel inventories) — one message, multiple tool calls.
- Communication. Evidence-first language ("the evidence shows", "unconfirmed, requires X to verify"). No hedging, no narrative.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 197 lines · 55 tokens per session scan A c544661dd73d
bmad-investigate is a skill published in the GitHub repository jeffrey2423/commit-like-pro (2 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 2,504 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to bmad-investigate, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
hunk-extensions
Maps the hunkdiff/extension authoring surface for Hunk, the terminal diff viewer — hiding or reordering reviewed files, docked panes, alternate file views, commands and key bindings, dialogs, workspace writes, themes, syntax languages, VCS backends, lifecycle events. Use when writing, debugging, or installing a Hunk…
shadow-verify
Dispatch a parallel adversarial verifier wave after any high-stakes sub-agent investigation (code reviews, audits, findings reports, large refactors, gap analyses) — or whenever a sub-agent asserts a claim with high-confidence language ("confident", "certain", "clearly", ≥80%), since confidence is a trigger, not a…
hatch3r-incident-response
Handles production incidents with structured triage, mitigation, and post-mortem. Use when responding to production issues, outages, or security incidents.
hatch3r-bug-fix
Step-by-step bug fix workflow. Diagnose root cause, implement minimal fix, write regression test. Use when fixing bugs, working on bug report issues, or when the user mentions a bug.
hatch3r-perf-audit
Profiles and optimizes application performance against defined budgets. Use when investigating performance issues, auditing performance budgets, or optimizing hot paths.
hatch3r-logical-refactor
Workflow for changing behavior or logic flow without adding new features or overhauling UI. Use when modifying business logic, data flows, behavioral rules, or working on logical refactor issues.