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/omkhar/vulnerability-validation-skill/vulnerability-validationnpx skills add omkhar/vulnerability-validation-skill --skill vulnerability-validationgit clone --depth 1 https://github.com/omkhar/vulnerability-validation-skillWhat 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 | $0.00149 | $0.07950 |
| Opus 5 | $0.00075 | $0.03975 |
| Sonnet 5 | $0.00030 | $0.01590 |
| Haiku 4.5 | $0.00015 | $0.00795 |
Grade A, and why
vulnerability-validation 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 — 450 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vulnerability Validation
Use this workflow to discover new vulnerabilities (0-days) in a target repository and validate them. By default it runs native discovery: with no findings list it analyzes the code to find vulnerabilities itself; a scanner finding, researcher report, or PoC is only an optional seed. Reduce every candidate to a defensible disposition, fix true issues with minimal idiomatic patches, and leave evidence another engineer can replay.
Quick Start
For target reads, PHASE-0 starts with an external operator-controlled verifier authenticating the whole package
outside the target and neutralizing project-local discovery before startup; the loaded package cannot attest itself.
Without both proofs, stop at documentation/package compatibility with no target read. After proof and operator
authorization, record run-state.bootstrap.json, then search AI-use/security policy, threat model/boundaries,
disclosure process, and upstream sources. Collect target repository/branch, latest upstream HEAD, baseline SHA,
dirty state, finding source type, frozen snapshot or seed sources/counts, artifact root, local-only validation
environment, dependency installation/provisioning method, upstream URL, repo commands, and output mode.
Read references/portable-invariants.md and create run-state.json before triage. For the default native
discovery run, load references/discovery-intake.md; optionally run scripts/discovery_engine.py for a
first pass,. Load references/artifact-contract.md when needed:
references/artifact-index.md, references/controlled-fields.md, references/closure-bundle.md,
references/drift-gate.md, references/evidence-bundle.md. Read references/review-lenses.md
before claiming review consensus and references/policy-friction.md when the LLM refuses or hedges.
What ships with it
26 files 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.
- references/artifact-contract.md 3.2 KB
- references/artifact-index.md 19 KB
- references/closure-bundle.md 7.6 KB
- references/controlled-fields.md 19 KB
- references/discovery-intake.md 27 KB
- references/discovery-orchestrator.md 5.5 KB
- references/discovery-playbooks.md 4.1 KB
- references/discovery-specialist-router.md 6.6 KB
- references/drift-gate.md 28 KB
- references/evidence-bundle.md 9.1 KB
- references/lane-heartbeat.md 6.5 KB
- references/loop-engineering.md 7.7 KB
- references/policy-friction.md 8.6 KB
- references/portable-invariants.md 48 KB
- references/project-plan-gate.md 2.1 KB
- references/promoted-replay-contract.md 13 KB
- references/proof-harness-router.md 3.0 KB
- references/review-lenses.md 22 KB
- references/sanitizer-selection.md 6.3 KB
- references/shadow-skill-bootstrap.md 4.4 KB
- references/surface-tool-inventory.md 4.6 KB
- references/tool-firewall.md 10 KB
- scripts/discovery_engine.py 75 KB runs code
- scripts/quarantine_extract.py 7.1 KB runs code
- scripts/surface_tool_inventory.py 5.6 KB runs code
- scripts/validate_artifact_bundle.py 475 KB runs code
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 · 450 lines · 149 tokens per session scan A 039d31bb8cae
vulnerability-validation is a skill published in the GitHub repository omkhar/vulnerability-validation-skill (5 stars, last pushed 9d ago), licensed Apache-2.0. It adds 149 tokens to every session and 7,950 once invoked, about $0.0007 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.
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