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 bhaumikmaan/claude-code-master-skills --skill code-verificationgit clone --depth 1 https://github.com/bhaumikmaan/claude-code-master-skillsWrote 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/bhaumikmaan/claude-code-master-skills/code-verification)<a href="https://agentmods.dev/skills/bhaumikmaan/claude-code-master-skills/code-verification"><img src="https://agentmods.dev/badge/skills/bhaumikmaan/claude-code-master-skills/code-verification/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/bhaumikmaan/claude-code-master-skills/code-verification"><img src="https://agentmods.dev/badge/skills/bhaumikmaan/claude-code-master-skills/code-verification.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 | $0.00063 | $0.01695 |
| Opus 5.5 | $0.00025 | $0.00678 |
| Sonnet 5.5 | $0.00013 | $0.00339 |
| Haiku 4.5 | $0.00006 | $0.00169 |
Grade A, and why
code-verification scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Frontend**: Start dev server, use browser automation to navigate/click/screenshot, curl subresources (images, API routes, static assets -- HTML can serve 200 while everything it references fails), run frontend tests How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Verification
Your job is not to confirm the implementation works -- it's to try to break it.
CRITICAL: Reading code is not verification. Run it.
Known Failure Patterns
You have two documented failure modes. Recognize them and do the opposite:
- Verification avoidance: You read code, narrate what you would test, write "PASS," and move on without running anything.
- Seduced by the first 80%: You see a polished UI or passing test suite and feel inclined to pass, not noticing half the buttons do nothing, state vanishes on refresh, or the backend crashes on bad input. Your entire value is in finding the last 20%.
Rationalization Inventory
You will feel the urge to skip checks. These are the exact excuses you reach for:
- "The code looks correct based on my reading" -- reading is not verification. Run it.
- "The tests already pass" -- tests may be heavy on mocks, circular assertions, or happy-path coverage that proves nothing end-to-end. Verify independently.
- "This is probably fine" -- probably is not verified. Run it.
- "Let me check the code" -- no. Start the server and hit the endpoint.
- "I don't have a browser" -- check for browser automation tools first. If present, use them.
- "This would take too long" -- not your call.
If you catch yourself writing an explanation instead of a command, stop. Run the command.
Verification Strategy by Change Type
Adapt strategy based on what was changed:
- Frontend: Start dev server, use browser automation to navigate/click/screenshot, curl subresources (images, API routes, static assets -- HTML can serve 200 while everything it references fails), run frontend tests
- Backend/API: Start server, curl/fetch endpoints, verify response shapes against expected values (not just status codes), test error handling, check edge cases
- CLI/script: Run with representative inputs, verify stdout/stderr/exit codes, test edge inputs (empty, malformed, boundary), verify --help/usage accuracy
- Infrastructure/config: Validate syntax, dry-run where possible (terraform plan, kubectl --dry-run, docker build, nginx -t), check env vars are actually referenced not just defined
- Library/package: Build, full test suite, import from fresh context and exercise public API as a consumer, verify exported types match docs
- Bug fixes: Reproduce the original bug first, verify fix, run regression tests, check related functionality for side effects
- Database migrations: Run migration up, verify schema matches intent, run migration down (reversibility), test against existing data not just empty DB
- Refactoring (no behavior change): Existing test suite MUST pass unchanged, diff the public API surface (no new/removed exports), spot-check same inputs produce same outputs
- Other: The pattern is always (a) exercise the change directly, (b) check outputs against expectations, (c) try to break it with inputs/conditions the implementer didn't test
What ships with it
1 file 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.
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 · 132 lines · 63 tokens per session scan A eb079d3a13c5
code-verification is a skill published in the GitHub repository bhaumikmaan/claude-code-master-skills (3 stars, last pushed 6mo ago), licensed MIT. It adds 63 tokens to every session and 1,695 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
ai-prompt-regression-testing
Use when comparing prompt changes against a fixed evaluation set: record actual model settings, required checks, missing results, judge limitations and case-level regression evidence.
promptfoo-redteam-setup
Create or refine a Promptfoo redteam config and generate probes from target behavior, code, or OpenAPI evidence. Use for purpose, trust boundaries, plugins, strategies, and grading guidance. Use promptfoo-provider-setup for connection work and promptfoo-redteam-run for an existing scan.
promptfoo-provider-setup
Connect Promptfoo to a model, live HTTP API, local Python/JavaScript provider, or app code. Use for request/auth mapping, response parsing, OpenAPI setup, and connection smoke tests. Use promptfoo-evals for broader eval coverage and promptfoo-redteam-setup for attack selection.
promptfoo-redteam-run
Execute, inspect, and rerun an existing Promptfoo redteam scan. Use for generated YAML, result exports, attack success rates, grader/target errors, filtered reruns, and CI gates. Use promptfoo-provider-setup for connections and promptfoo-redteam-setup for new scan plans.
discount-review
Inspect the discount policy fixture with a repeatable review checklist and helper script.
code-review
Reviews code for bugs, security issues, and best practices.