Archon is a workflow engine for AI coding agents that turns development processes into YAML-defined sequences with phases, validation gates, and artifacts. Developers use it to run repeatable processes such as planning, implementation, testing, code review, and pull-request creation across projects. The catalogue entries provide commands, agents, skills, hooks, instructions, and settings for working with Archon.
Borrowing it
Nothing to install: this file belongs to coleam00/Archon. 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/coleam00/Archon/dev/.github/prompts/investigate-debug.prompt.mdgit clone --depth 1 https://github.com/coleam00/ArchonWrote 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/commands/coleam00/archon/investigate-debug)<a href="https://agentmods.dev/commands/coleam00/archon/investigate-debug"><img src="https://agentmods.dev/badge/commands/coleam00/archon/investigate-debug/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/commands/coleam00/archon/investigate-debug"><img src="https://agentmods.dev/badge/commands/coleam00/archon/investigate-debug.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 | $0.00020 | $0.03106 |
| Opus 5 | $0.00010 | $0.01553 |
| Sonnet 5 | $0.00004 | $0.00621 |
| Haiku 4.5 | $0.00002 | $0.00311 |
Grade A, and why
investigate-debug 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 today.
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 — 529 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigate Issue
Input: ${input:issue:GitHub issue number, URL, or problem description}
Your Mission
Investigate the issue/problem and produce a comprehensive implementation plan that:
- Can be executed by
/implement-fix - Is posted as a GitHub comment (if GH issue provided)
- Captures all context needed for one-pass implementation
Golden Rule: The artifact you produce IS the specification. The implementing agent should be able to work from it without asking questions.
Phase 1: PARSE - Understand Input
1.1 Determine Input Type
| Input | Example | Action |
|---|---|---|
| Issue number | 123, #123 |
Fetch with gh issue view |
| URL | github.com/.../issues/123 |
Extract number, fetch |
| Free-form text | anything else | Use as problem description |
| Blank | (none) | Use conversation context |
If GitHub issue:
gh issue view {number} --json title,body,labels,comments,state,url,author
1.2 Extract Context
If GitHub issue:
- Title: What's the reported problem?
- Body: Details, reproduction steps, expected vs actual
- Labels: bug? enhancement? documentation?
- Comments: Additional context from discussion
- State: Is it still open?
If free-form:
- Parse as problem description
- Note: No GitHub posting (artifact only)
1.3 Classify Issue Type
| Type | Indicators |
|---|---|
| BUG | "broken", "error", "crash", "doesn't work", stack trace |
| ENHANCEMENT | "add", "support", "feature", "would be nice" |
| REFACTOR | "clean up", "improve", "simplify", "reorganize" |
| CHORE | "update", "upgrade", "maintenance", "dependency" |
| DOCUMENTATION | "docs", "readme", "clarify", "example" |
1.4 Assess Severity/Priority, Complexity, and Confidence
Each assessment requires a one-sentence reasoning based on concrete findings.
For BUG issues - Severity:
| Severity | Criteria |
|---|---|
| CRITICAL | System down, data loss, security vulnerability, no workaround |
| HIGH | Major feature broken, significant user impact, difficult workaround |
| MEDIUM | Feature partially broken, moderate impact, workaround exists |
| LOW | Minor issue, cosmetic, edge case, easy workaround |
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.
- today First seen · 529 lines · 20 tokens per session scan A 25a93d26ce9e
investigate-debug is a command published in the GitHub repository coleam00/Archon (23,398 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 3,106 once invoked, about $0.0001 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 2026-09-08.
Other commands, from other repositories
fix-issues
Diagnose, reproduce, then fix reproducible open GitHub issues in parallel: one clean worktree/issue; symlink build artifacts to avoid rebuilds.
cleanup
Autonomous cleanup-loop iteration: discover ONE target → complete execution → verify → report. Runs stateless: derive from current tree; assume prior runs left it consistent.
hatch3r-diagnose
Troubleshoot a hatch3r framework issue (setup, config, adapter wiring, drift). Gathers state, delegates root-cause analysis to hatch3r-researcher, proposes a fix, and applies it via hatch3r-fixer after one confirmation gate.
auto-fix
A bug-fixing command that focuses on reproducing a problem and making the smallest suitable code change.
refactor-cleanup.template
This prompt was authored for Claude-style slash workflows. In Codex runtime, adapt tool calls as follows.
ui-fix.template
This prompt was authored for Claude-style slash workflows. In Codex runtime, adapt tool calls as follows.