openlore-debug

A debugging workflow that uses OpenLore's code-structure context, an explicit explanation of the likely root cause, and RED/GREEN checks to verify the repair.

In plain words
What is it for?
Diagnosing and repairing bugs, unexpected behaviour, and regressions in codebases that already have OpenLore analysis available.
Why use it?
It gives bug fixing a reproducible starting point and requires evidence that the change addresses the reported failure.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/clay-good/openlore/openlore-debug
Any agent
npx skills add clay-good/OpenLore --skill openlore-debug
Clone the repo
git clone --depth 1 https://github.com/clay-good/OpenLore

Made for: Claude Code, Codex.

Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,164 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.02164
Opus 5 $0.00019 $0.01082
Sonnet 5 $0.00008 $0.00433
Haiku 4.5 $0.00004 $0.00216

Measured 2d ago against content hash ed6dd10ca142, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

openlore-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 2d 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.

examples/mistral-vibe/skills/openlore-debug/SKILL.md · 290 lines

How it starts

The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.

openlore: Debug

When to use this skill

Trigger this skill when the user reports a bug or unexpected behaviour on a codebase that has openlore analysis available, with phrasings like:

  • "this is broken"
  • "X is not working"
  • "something is wrong with Y"
  • "debug this"
  • explicit command /openlore-debug

The rule: form an explicit hypothesis before reading any code. Do not browse files speculatively.

Prerequisite: openlore analysis must exist (openlore analyze has been run). If orient returns "error": "no cache" → run analyze_codebase first, then retry.


Step 1 — Reproduce

Ask the user for:

  1. Steps to reproduce — minimal sequence that triggers the bug
  2. Expected behaviour — what should happen
  3. Observed behaviour — what actually happens
  4. $PROJECT_ROOT — project root directory

Do not proceed to Step 2 until all four are known.

If the user cannot reproduce the bug reliably, note it and proceed anyway — but flag that the fix may be speculative until reproduction is confirmed.

Capture:

  • $BUG_DESCRIPTION — one-line summary of the symptom (e.g. "payment retry does not reset counter after success")
  • $REPRO_STEPS — reproduction sequence

Step 2 — Orient

Call the openlore MCP tool orient with:

{
  "directory": "$PROJECT_ROOT",
  "task": "$BUG_DESCRIPTION",
  "limit": 7
}

Extract:

  • $CANDIDATE_FUNCTIONS — top 3–5 functions structurally related to the symptom
  • $DOMAINS_AFFECTED — spec domains involved
  • $CALL_PATHS — call chains relevant to the symptom

Step 3 — Search specs

If openspec/specs/ exists:

Call the openlore MCP tool search_specs with:

{
  "directory": "$PROJECT_ROOT",
  "query": "$BUG_DESCRIPTION",
  "limit": 5
}

Look for:

  • Documented constraints that the buggy behaviour violates
  • Requirements that define what "correct" means for $DOMAINS_AFFECTED
  • Known edge cases documented in the spec that may explain the symptom

Read the full file on GitHub · 290 lines

Changes

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.

  1. 2d ago First seen · 290 lines · 39 tokens per session scan A ed6dd10ca142

Subscribe to this mod's changes

openlore-debug is a skill published in the GitHub repository clay-good/OpenLore (290 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 2,164 once invoked, about $0.0002 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 2026-08-30.

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