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 agentmods add skills/clay-good/openlore/openlore-debugnpx skills add clay-good/OpenLore --skill openlore-debuggit clone --depth 1 https://github.com/clay-good/OpenLoreWhat 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 | $0.00039 | $0.02164 |
| Opus 5 | $0.00019 | $0.01082 |
| Sonnet 5 | $0.00008 | $0.00433 |
| Haiku 4.5 | $0.00004 | $0.00216 |
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.
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:
- Steps to reproduce — minimal sequence that triggers the bug
- Expected behaviour — what should happen
- Observed behaviour — what actually happens
$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
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.
- 2d ago First seen · 290 lines · 39 tokens per session scan A ed6dd10ca142
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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