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 clay-good/OpenLore --skill openlore-review-changesgit clone --depth 1 https://github.com/clay-good/OpenLoreWrote 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/clay-good/openlore/openlore-review-changes)<a href="https://agentmods.dev/skills/clay-good/openlore/openlore-review-changes"><img src="https://agentmods.dev/badge/skills/clay-good/openlore/openlore-review-changes/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/clay-good/openlore/openlore-review-changes"><img src="https://agentmods.dev/badge/skills/clay-good/openlore/openlore-review-changes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00044 | $0.01183 |
| Opus 5.5 | $0.00018 | $0.00473 |
| Sonnet 5.5 | $0.00009 | $0.00237 |
| Haiku 4.5 | $0.00004 | $0.00118 |
Grade A, and why
openlore-review-changes 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 2mo 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
openlore: Review Changes
When to use this skill
Trigger this skill whenever the user asks to review, audit, or check the safety of recent changes, with phrasings like:
- "review my changes"
- "what did I break?"
- "is this branch safe to merge?"
- "pre-PR check"
- "what's risky in this diff?"
- "check the blast radius of my changes"
- explicit command
/openlore-review-changes
No code is written. Output is a risk-ranked review with a go/no-go recommendation.
Step 1 — Confirm directory and base ref
Ask: which project? Diff against which base? (default: main)
Store as $DIRECTORY and $BASE_REF.
Step 2 — Detect changed functions and risk scores
Call the openlore MCP tool detect_changes with:
{"directory": "$DIRECTORY", "base": "$BASE_REF"}
The risk score is multiplicative: likelihood × impact.
likelihood= how much was changed × how poorly covered it is ("called"tests count full;"imported"-only count 0.3×)impact= structural blast radius (log fanIn + distance-weighted transitive callers weighted by callType + external boundary calls)
A function with fanIn=0 calling nothing external scores 0 regardless of change size — correct; focus on non-zero scores.
Present a risk-ranked table:
| Rank | Function | File | riskScore | blastRadius | fanIn | testedBy |
|---|
Flag:
riskScore ≥ 5→ 🔴 HIGH — must inspectriskScore 2–5→ 🟡 MEDIUM — inspect if time allowsriskScore < 2→ 🟢 LOW
Step 3 — Deep-inspect each HIGH function
For each function with riskScore ≥ 5, call get_minimal_context:
{"directory": "$DIRECTORY", "functionName": "$FUNCTION_NAME"}
What to read:
function.riskLevel—"high"means the tool expanded caller/callee lists to 24. All shown entries are in the blast radius.callers[*].callType— all"awaited"= async interface frozen; any signature change breaks every caller without a compile error in JS. Mixed = looser coupling.callees[*].isExternal: true— function touches an external boundary (HTTP/DB). Failures here propagate outward and may not be caught in unit tests.testedBy[*].confidence—"called"= direct test (strong safety net)."imported"= test file only imports the module;vi.mock()can neutralize it entirely. Only"imported"= effectively untested.
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.
- 2mo ago First seen · 133 lines · 44 tokens per session scan A ce058667322f
openlore-review-changes is a skill published in the GitHub repository clay-good/OpenLore (358 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 1,183 once invoked, about $0.0002 per session on Opus 5.5. 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.
openlore-review-changes compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| openlore-review-changesclay-good/OpenLore | Skill | 358 | today | MIT | A | 44 | Claude Code, Codex |
| nw-fp-usable-designnWave-ai/nWave | Skill | 633 | today | MIT | A | 20 | Claude Code |
| nw-review-workflownWave-ai/nWave | Skill | 633 | today | MIT | A | 21 | Claude Code |
| architecture-reviewludo-technologies/pyscn | Skill | 1.1k | today | MIT | A | 53 | Claude Code |
| refactoringludo-technologies/pyscn | Skill | 1.1k | today | MIT | A | 52 | Claude Code |
| nw-code-design-oonWave-ai/nWave | Skill | 633 | today | MIT | A | 52 | Claude Code, Codex |
| pre-pushAlexZio00/sovereign-skills | Skill | 157 | yesterday | MIT | A | 166 | Claude Code, Codex |