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 mattmre/EVOKORE-MCP-PUBLIC --skill triage-buggit clone --depth 1 https://github.com/mattmre/EVOKORE-MCP-PUBLICWrote 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/mattmre/evokore-mcp-public/triage-bug)<a href="https://agentmods.dev/skills/mattmre/evokore-mcp-public/triage-bug"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/triage-bug/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/mattmre/evokore-mcp-public/triage-bug"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/triage-bug.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 | $0.00060 | $0.01832 |
| Opus 5 | $0.00030 | $0.00916 |
| Sonnet 5 | $0.00012 | $0.00366 |
| Haiku 4.5 | $0.00006 | $0.00183 |
Grade A, and why
triage-bug 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.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
triage-bug — Triage a Bug From Evidence, Not From a User
When to use this skill
Use when there is a bug signal that needs root-cause analysis and a TDD fix plan, and the source of that signal is not a live user description. EVOKORE-MCP is agent-driven; bugs surface through:
tool_errorrows in~/.evokore/sessions/*-evidence.jsonltest_failurerows in~/.evokore/sessions/*-evidence.jsonl- abnormal call sequences in
~/.evokore/sessions/*-replay.jsonl - branch / worktree / control-plane drift surfaced by
npm run repo:audit - telemetry anomalies via the
get_telemetrynative tool
If a human reported the bug verbally and the signal hasn't been captured
yet, escalate to HITL: stop, ask the orchestrator to file a
triage:new issue, and re-enter this skill once evidence rows exist.
Adapted From Upstream
This skill is adapted from mattpocock/skills/triage-bug (upstream
commit 90ea8eec03d4ae8f43427aaf6fe4722653561a42, MIT-licensed). The
upstream skill assumes a user describes the bug, the agent asks
clarifying questions, and the user confirms reproduction steps.
EVOKORE-MCP is agent-driven, so all of those steps are replaced with
artifact reads.
EVOKORE-Specific Adaptations
| Upstream behavior | EVOKORE behavior |
|---|---|
| "Ask the user to describe the bug" | Read most recent ~/.evokore/sessions/*-evidence.jsonl for tool_error / test_failure rows |
| "Ask the user for reproduction steps" | Read corresponding ~/.evokore/sessions/*-replay.jsonl for the call sequence leading up to the failure (timestamp window before the error row) |
| "Ask the user about environment" | Run npm run repo:audit for branch/worktree drift; optionally call get_telemetry native tool for runtime context |
| "Iterate with user on root cause hypothesis" | Invoke panel-of-experts skill with persona set [debugger, architect, qa-lead] if the root cause crosses bounded contexts (ADR-0005) |
| "User confirms the fix plan" | The fix plan is a TDD plan (failing test path + expected assertion + fix surface) written to docs/bugs/<slug>.md; the actual confirmation is the failing test commit produced by the downstream tdd skill |
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 · 166 lines · 60 tokens per session scan A 04a98f902bf3
triage-bug is a skill published in the GitHub repository mattmre/EVOKORE-MCP-PUBLIC (3 stars, last pushed 3mo ago), licensed MIT. It adds 60 tokens to every session and 1,832 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 2026-09-03.
Other skills, from other repositories
fix
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behavior-contract
Bug condition/postcondition formalization as testable Behavior Contracts. Defines invariants that must be preserved across fixes.
nw-bugfix
Bug fix workflow: root cause analysis → user review → regression test + fix via TDD.
debug
Use when something is broken — a failing or flaky test, crash, wrong result or regression — and the root cause must be reproduced and proven before any fix. On-demand; callable mid-implement. NOT a feature to spec or build (that is specify/implement), NOT the lint/test gate (that is verify), NOT adversarial diff…
test-writing
Writes meaningful tests that actually catch bugs.
debugging
A structured method for finding and fixing software bugs. It starts by writing a test that reproduces the failure, then investigates its underlying cause before making a small fix.