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 skills add SyloRei/claude-godmode --skill triagegit clone --depth 1 https://github.com/SyloRei/claude-godmodeWrote 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/sylorei/claude-godmode/triage)<a href="https://agentmods.dev/skills/sylorei/claude-godmode/triage"><img src="https://agentmods.dev/badge/skills/sylorei/claude-godmode/triage/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/skills/sylorei/claude-godmode/triage"><img src="https://agentmods.dev/badge/skills/sylorei/claude-godmode/triage.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 | $0.00051 | $0.01322 |
| Opus 5 | $0.00026 | $0.00661 |
| Sonnet 5 | $0.00010 | $0.00264 |
| Haiku 4.5 | $0.00005 | $0.00132 |
Grade A, and why
triage 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 9d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Triage
Respond to a live production incident — an outage, a regression, or unexpected behavior reported from the field. Establish what happened and how bad it is BEFORE touching code. This skill triages; it does not write the fix.
Auto Mode
Auto Mode suppresses confirmation prompts and proceed-pauses — not the one
clarifying question that can matter here: when it started, when it was last
known-good, or who reported it is unknown, don't ask blank — lead with your
best-inferred answer to override (e.g. "I'll take the incident start as the
first error at 14:02 UTC — correct me if it began earlier"), since triaging the
wrong incident wastes the whole effort. This clarifying question follows the
shared recommendation convention (godmode:recommend-convention) defined in
rules/godmode-recommend.md. Once the symptom is anchored, proceed: reconstruct
the timeline, assess blast radius, and route the fix without pausing. Treat
course-corrections as normal input.
The Job
- Establish the timeline
- Assess blast radius
- Reconstruct with cited evidence via
@incident-responder - Route the confirmed fix
Do NOT skip to the fix. Understand the incident first.
Step 1: TIMELINE
- What is the first observed symptom? (error, alert, user report)
- When did it start? When was the system last known-good?
- What changed in that window? (deploys, config, dependency, traffic)
Output: "Symptom [X] first seen at [time]. Last known-good [time]. Changed in window: [Y]."
Step 2: BLAST RADIUS
- Who and what is affected? (users, endpoints, regions, downstream systems)
- How severe is it? (full outage, degraded, single feature, cosmetic)
- Is it still ongoing or self-resolved?
Output: "Affected: [scope]. Severity: [level]. Status: [ongoing/resolved]."
Step 3: RECONSTRUCT (spawn @incident-responder)
Spawn @incident-responder (read-only) to reconstruct the timeline against the
code and recommend remediation with cited evidence. It investigates; it does
not change code.
What ships with it
1 file 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.
- 9d ago First seen · 141 lines · 51 tokens per session scan A 557c97a2e674
triage is a skill published in the GitHub repository SyloRei/claude-godmode (3 stars, last pushed 3mo ago), licensed MIT. It adds 51 tokens to every session and 1,322 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
debugging-protocol
Systematic protocol for diagnosing broken behavior and making recurrence structurally impossible. Schema mismatch causes 80% of bugs. Use when something isn't showing, isn't working, or is still broken after a fix attempt.
incident-response
Use when production is down, an alert fires, or an incident needs triage. Covers severity classification, communication, timeline tracking, and blameless postmortem with 5 whys. Also use after resolution to write the postmortem.
code-hygiene
Review your codebase for drift introduced by isolated AI sessions: dead exports, duplicate logic, and orphaned types.
performance
Use when code is slow, queries are taking too long, or you suspect N+1 queries, O(n squared) loops, missing indexes, or unbounded result sets.
diagnosing-bugs
Diagnosis loop for hard bugs and performance regressions. Builds a red-capable feedback loop and runs it before hypothesising — complements static code review (which finds bugs by reading) by running actual repros. Use when the user says 'diagnose'/'debug this', or reports something broken/throwing/failing/slow.
issue-debugging
Systematic methodology for issue debugging including root cause analysis, impact mapping, tiered validation plans, and confidence assessment. Use when analyzing bugs, fixing issues, or validating fixes.