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/mountainunicorn/add/verifynpx skills add MountainUnicorn/add --skill verifygit clone --depth 1 https://github.com/MountainUnicorn/addWhat 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 | $0.00021 | $0.04313 |
| Opus 5 | $0.00010 | $0.02157 |
| Sonnet 5 | $0.00004 | $0.00863 |
| Haiku 4.5 | $0.00002 | $0.00431 |
Grade A, and why
verify 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 — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADD Verify Skill v{{VERSION}}
Execute quality gates to verify code meets production standards. This skill runs automated checks and produces a structured pass/fail report.
Overview
The Verify skill is the final checkpoint before deployment. It runs a sequence of quality gates determined by context and provides clear go/no-go status for each gate. Output is a structured report with pass/fail status and next steps.
The five-gate system ensures code quality at every stage:
- Gate 1 (Local): Lint & code formatting
- Gate 2 (Local): Type checking (if applicable)
- Gate 3 (CI): Unit tests & coverage
- Gate 4 (Deploy): Spec compliance & integration tests
- Gate 5 (Smoke): Post-deploy health checks
All gate results are reported using the shared formats in ${CLAUDE_PLUGIN_ROOT}/templates/verify-report.md — one per-gate format, the maturity-scaled sections, and the overall report.
Pre-Flight Checks
-
Read .add/config.json
- Load gate definitions: which commands to run, thresholds
- Load ci.gates array (ordered list of gates)
- Load test.minCoverage threshold (default 80%)
- Load code.lint configuration
- Load code.types configuration
- Load environment tier settings
- A configuration example lives in
${CLAUDE_PLUGIN_ROOT}/templates/verify-report.md
-
Count active rules for maturity level
- Read maturity level from
.add/config.json(default: alpha) - Scan all files in
rules/directory - For each rule file, read the YAML frontmatter
maturity:field - Count rules where the maturity field is at or below the current level
- Maturity hierarchy: poc < alpha < beta < ga
- A rule with
maturity: pocis active at all levels - A rule with
maturity: betais active at beta and ga only
- Include in report header: "{N} rules active at {maturity} level"
- Read maturity level from
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 · 433 lines · 21 tokens per session scan A 6f6ce5f9e290
verify is a skill published in the GitHub repository MountainUnicorn/add (11 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 4,313 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
swarm
Launching multi-agent parallel work with the Agentic SDLC. Use when a task benefits from decomposition into parallel subtasks.
finish
Completing a development branch for merge readiness. Use when implementation and tests pass and the branch needs formal preparation for review and merge.
grill
Interrogating requirements to validate before building. Use before swarm decomposition, design decisions on ambiguous features, or when scope creep risk is high.
team
Referencing the agent roster, roles, coordination model, and dispatch modes. Use when spawning agents or checking permissions.
ticket
Associate every PDS task with a GitHub issue. Orchestrator finds or creates the ticket, posts plan and acceptance criteria as a checkbox list, updates it as work progresses. Use at Phase 1 of every swarm.
triage
Triage insights into actionable GitHub issues across repos. Use after running /insights to convert analysis into tracked work.