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 nearform/lastlight --skill verifygit clone --depth 1 https://github.com/nearform/lastlightWrote 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/nearform/lastlight/verify)<a href="https://agentmods.dev/skills/nearform/lastlight/verify"><img src="https://agentmods.dev/badge/skills/nearform/lastlight/verify/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/nearform/lastlight/verify"><img src="https://agentmods.dev/badge/skills/nearform/lastlight/verify.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 | $0.00060 | $0.01268 |
| Opus 5.5 | $0.00024 | $0.00507 |
| Sonnet 5.5 | $0.00012 | $0.00254 |
| Haiku 4.5 | $0.00006 | $0.00127 |
Grade A, and why
verify 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.
> stdout/stderr, `curl` against a dev-server you start, log excerpts, file How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verify
Test a specific claim about behaviour and report whether the evidence supports or refutes it. The deliverable is a verdict with evidence, not an opinion.
This skill uses the building skill for installing dependencies and running the repo's build/test commands in the sandbox.
Scope (text-evidence path). In the default text phase the sandbox agent has bash, file read, and the github tools — no browser, no screenshots, no video. Prove claims with what bash can capture: test output, command stdout/stderr,
curlagainst a dev-server you start, log excerpts, file contents, exit codes. Driving a real browser and attaching screenshots is the separatebrowser-qaskill, which is staged only in the gated browser phase running on the docker QA image (Playwright + Chromium). If that skill isn't in your catalogue and a claim genuinely can only be shown in a rendered UI, say so under INCONCLUSIVE rather than guessing — the browser phase will pick it up when available.
Ground rule — investigator, not advocate
Your job is to find out whether the claim is true, not to make it look true. A conclusive "this is broken" with clear evidence is exactly as valuable as a "this works". Specifically:
- Never fabricate, hardcode, mock, or stage evidence to match an expected outcome. Do not edit the code under test to make a result appear.
- If the behaviour you observe contradicts the claim, that is the result — report it as REFUTED with the evidence inline. Don't bury it.
- Don't retry a failing test hoping for a different answer. Retry only after changing the environment or procedure (wrong branch, missing build step), and only when you have reason to believe the test setup — not the code — was wrong. One unexpected result that reproduces is a finding.
Parse the target
The Context block gives you the claim and (usually) a PR or issue. The claim may arrive as:
- A direct claim — "ESC cancels streaming in bash mode", "the
--forkflag creates a new session". - A PR reference + claim — verify the claim against that PR's head.
- A PR reference only — read the PR description + diff and identify the most important, most testable claim it makes; state which claim you chose.
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 · 119 lines · 60 tokens per session scan A 964f2ccab7f0
verify is a skill published in the GitHub repository nearform/lastlight (40 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 1,268 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
benchmark-design
Design and calibrate a multi-Case capability Benchmark and establish a traceable Formal Baseline, or import a published Benchmark package.
agent-evaluation
Run one specified Test Agent on one specified Benchmark Case exactly once, privately score that execution, and return one protocol result.
agent-optimization
Improve an Agent State through versioned scores and score-linked Traces from a frozen Benchmark.
analyze-task
Check OSWorld tasks. Validate the evaluation function, verify that the instruction is feasible given the task setup and agent-visible files, inspect setup artifacts when needed, and produce both markdown and structured JSON reports.
review
Review a small code change for correctness and missing tests.
orca
Use when the user asks to run an Orca flow (e.g. "use orca to implement …"), or when delegating a well-defined implementation task to Orca's autonomous multi-agent flow — a headless plan-code-review CLI to hand a coding task to instead of implementing it yourself.