rtl-p5s-coverage-policy

rtl-p5s-coverage-policy is a skill for Claude Code from babyworm/rtl-agent-team. It costs 25 tokens per session (2,719 once invoked), scanned A, original, MIT.

An internal rule set for analysing coverage from RTL functional verification. It defines coverage targets, repeated analysis and test-generation rounds, and how to document unreachable areas.

In plain words
What is it for?
Use it when reviewing or closing coverage for RTL tests. It covers line, signal-toggle, and finite-state-machine coverage, gap prioritisation, additional tests, and waiver documentation.
Why use it?
It gives teams a consistent way to decide whether coverage gaps need tests or justified exclusions. It also keeps raw results visible alongside results after exclusions.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the rtl-agent-team plugin — 97 skills, 99 agents, 6 hooks shipped together

Good fit Use it when reviewing or closing coverage for RTL tests. It covers line, signal-toggle, and finite-state-machine coverage, gap prioritisation, additional tests, and waiver documentation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/babyworm/rtl-agent-team/rtl-p5s-coverage-policy
Install

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.

Any agent
npx skills add babyworm/rtl-agent-team --skill rtl-p5s-coverage-policy
Clone the repo
git clone --depth 1 https://github.com/babyworm/rtl-agent-team

Made for: Claude Code.

Or install rtl-agent-team, the plugin that ships this one along with the rest of its 97 skills, 99 agents, 6 hooks.

Wrote 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.

agentmods badge for rtl-p5s-coverage-policy

README.md
[![agentmods](https://agentmods.dev/badge/skills/babyworm/rtl-agent-team/rtl-p5s-coverage-policy/github.svg)](https://agentmods.dev/skills/babyworm/rtl-agent-team/rtl-p5s-coverage-policy)
Your own site
<a href="https://agentmods.dev/skills/babyworm/rtl-agent-team/rtl-p5s-coverage-policy"><img src="https://agentmods.dev/badge/skills/babyworm/rtl-agent-team/rtl-p5s-coverage-policy/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.

agentmods 80×15 button for rtl-p5s-coverage-policy

Your own site · 80×15
<a href="https://agentmods.dev/skills/babyworm/rtl-agent-team/rtl-p5s-coverage-policy"><img src="https://agentmods.dev/badge/skills/babyworm/rtl-agent-team/rtl-p5s-coverage-policy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,719 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00025 $0.02719
Opus 5.5 $0.00010 $0.01088
Sonnet 5.5 $0.00005 $0.00544
Haiku 4.5 $0.00003 $0.00272

Measured 20d ago against content hash 2e8573408979, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

rtl-p5s-coverage-policy 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 20d 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.

skills/rtl-p5s-coverage-policy/SKILL.md · 225 lines

How it starts

The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Coverage Analysis Policy

Coverage Targets

Metric Target Evaluated On
Line coverage ≥ 90% Post-exclusion
Toggle coverage ≥ 80% Post-exclusion
FSM coverage ≥ 70% Post-exclusion

Raw coverage is always reported alongside post-exclusion numbers for transparency.

Coverpoint Iterative Refinement (minimum 3 rounds)

Coverage coverpoint extraction and test generation must iterate at least 3 times:

  • Round 1 (Initial Analysis): Identify all uncovered lines, branches, FSM states/transitions. Prioritize gaps (HIGH/MED/LOW). Generate first batch of directed tests for HIGH gaps.
  • Round 2 (Deepen): Re-analyze coverage after Round 1 tests. Identify newly reachable but still uncovered paths. Add cross-coverage points (e.g., cmd × size, state × error). Target MED gaps. Check for unreachable code (waiver candidates).
  • Round 3 (Close): Final coverage push. Add corner-case stimulus for remaining gaps. Verify coverage targets met (line ≥ 90%, toggle ≥ 80%, FSM ≥ 70%). Document waived bins with justification.
  • Additional rounds: Continue until coverage targets are met or all remaining gaps are justified as waived.

Each round produces a progress note at .rat/scratch/phase-5/coverage-iteration-r{N}.md.

Escalation & Stop Conditions

  • LOW priority gaps flagged as unreachable → report to user, recommend dead code removal
  • Coverage tool format unrecognized → halt, ask user for coverage format (Icarus, VCS, etc.)
  • Coverage below 70% after gap fill → escalate to rtl-architect for structural review

Final Checklist

  • sim/coverage/coverage_gaps.md written with all gaps prioritized
  • New tests written for all HIGH priority gaps
  • Coverage improvement measured and reported
  • Unreachable code gaps flagged separately

CDTG Feedback Protocol (Coverage → Testbench-Dev)

When coverage-analyst identifies HIGH/CRITICAL gaps, it must produce a Directed Test Guidance table that testbench-dev can directly consume. This closes the Coverage-Driven Test Generation loop with structured, actionable feedback — not just gap descriptions.

Read the full file on GitHub · 225 lines

Changes

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.

  1. 20d ago First seen · 225 lines · 25 tokens per session scan A 2e8573408979

Subscribe to this mod's changes

rtl-p5s-coverage-policy is a skill published in the GitHub repository babyworm/rtl-agent-team (61 stars, last pushed 21d ago), licensed MIT. It adds 25 tokens to every session and 2,719 once invoked, about $0.0001 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 2026-10-08.

Related

Other skills, from other repositories

building-pydantic-ai-agents

Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), workspaces, structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydanticai, or asks to build an AI agent, add tools/capabilities, attach a workspace, defer capability…

pydantic/pydantic-ai · 92 tokens

verification-strategy

Thorough verification of completed work before declaring done.

vstorm-co/pydantic-deepagents · 13 tokens

image-compare

Compare two image files on disk and report what changed, region by region. Trigger on "what changed between these two images", "diff these PNGs", "did this render drift", "compare screenshots/exports/renders".

teimurjan/blazediff · 49 tokens

test-sqrl

Use when adding or updating tests for a DataSQRL pipeline. Use after implementing features to verify correctness.

DataSQRL/sqrl · 26 tokens

qa-review

QA review for code changes — test coverage analysis, edge case identification, test plan generation, regression detection, test health tracking over time.

suyoumo/ClawProBench · 30 tokens

lastlight-evals-loop

Drive a Last Light EVAL toward a target score with a disciplined, anti-gaming improvement loop — run → mine failures → propose candidate fix(es) → re-measure → keep the best or revert → repeat. Use when the user wants to "improve / raise the pr-review F1", "make the reviewer better against the eval", "close the loop…

nearform/lastlight · 200 tokens