Borrowing it
Nothing to install: this file belongs to omkhar/vulnerability-validation-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/omkhar/vulnerability-validation-skill/main/AGENTS.mdgit clone --depth 1 https://github.com/omkhar/vulnerability-validation-skillWrote 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/instructions/omkhar/vulnerability-validation-skill/agents-md)<a href="https://agentmods.dev/instructions/omkhar/vulnerability-validation-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/omkhar/vulnerability-validation-skill/agents-md/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/instructions/omkhar/vulnerability-validation-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/omkhar/vulnerability-validation-skill/agents-md.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 | $0.02535 | $0.02535 |
| Opus 5.5 | $0.01014 | $0.01014 |
| Sonnet 5.5 | $0.00507 | $0.00507 |
| Haiku 4.5 | $0.00253 | $0.00253 |
Grade A, and why
vulnerability-validation-skill AGENTS.md 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 1mo 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Working Agreement
This repository packages one portable vulnerability-validation Agent Skill.
This skill discovers and validates vulnerabilities. Its default mode is native discovery:
presented a target repository with no findings list (finding_source_type = native_discovery),
it analyzes the code to find new vulnerabilities (0-days) itself, then drives every candidate
through the existing validation machinery. A supplied scanner finding, researcher report, or PoC
is an optional seed, not a prerequisite. Discovery is a gated precursor: it enumerates and
ranks candidates but never dispositions a finding or computes severity at intake; only the
existing validation gates (reachability, live PoC, negative control, threat-model fit, and
fixed-build differential evidence) promote a candidate to a finding. The discovery methodology is
mandated and documented in
skill-core/references/discovery-intake.md; it is bounded by a declared stopping criterion,
admits nothing to a maintainer without proof, and may never claim finding-space completeness. The
canonical body stays a lean orchestration spine: discovery method detail lives in references, while
scripts/discovery_engine.py may deterministically generate and rank candidate ledgers. The engine
is a candidate source only: it cannot disposition findings, compute final severity, patch code, or
produce maintainer-facing vulnerability claims.
A dev-only discovery-accuracy regression oracle (scripts/efficacy_oracle.py, fixtures under
tests/eval/, methodology in docs/accuracy-eval-methodology.md) is permitted under this charter.
It is a discrimination-regression measurement that runs the repository's existing deterministic
gates over labeled SYNTHETIC fixtures to confirm they still block planted false positives, admit
sound true positives, and protect discovery recall (no silent candidate drops, no false
completeness claims); it encodes no real target or finding, and it generates and ranks no
candidates itself.
A separate dev-only native candidate-generation oracle (scripts/discovery_engine_oracle.py,
fixtures and baseline under tests/engine_eval/) may execute the real engine over pinned synthetic
known-sink targets. It measures planted-target recall, cap survival, candidate burden, negative-
control emissions, deterministic work units, and replay stability. These metrics are regression
evidence for the committed heuristic corpus only, never real-world vulnerability recall, candidate
validation, finding promotion, or finding-space completeness.
An autonomous discovery engine (scripts/discovery_engine.py) is also permitted under this
charter. It inspects a local target repository, optionally provisions tools only into a run-local
tool home, falls back to deterministic source heuristics when tools fail, and emits native
discovery ledgers (discovery-plan.json, surface-inventory.json,
discovery-lane-results.json, candidate-fusion.json). Its output is unvalidated candidate input
for the existing gates, never a maintainer-ready report.
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.
- 1mo ago First seen · 171 lines · 2,535 tokens per session scan A 69c8be9e02e6
vulnerability-validation-skill AGENTS.md is an instructions file published in the GitHub repository omkhar/vulnerability-validation-skill (7 stars, last pushed yesterday), licensed Apache-2.0. It adds 2,535 tokens to every session, about $0.0101 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 2026-08-31.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.