regression-sweep

regression-sweep is a skill for Claude Code from transilienceai/communitytools. It costs 43 tokens per session (1,103 once invoked), scanned A, original, MIT.

A scheduled security check that reruns previously confirmed vulnerability tests and compares the results with earlier evidence. It also checks whether the related CVE, a public record of a security flaw, has changed severity.

In plain words
What is it for?
Walking through validated security findings, rerunning their proof-of-concept tests, saving new evidence, comparing results, checking CVE severity, and classifying findings as still valid, changed in severity, or no longer exploitable.
Why use it?
It detects when a vulnerability has been fixed, weakened, or accidentally introduced again. This helps keep old security findings accurate after code or dependency changes.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the communitytools plugin — 48 skills, 5 commands, 9 agents, 1 hook shipped together

Good fit Walking through validated security findings, rerunning their proof-of-concept tests, saving new evidence, comparing results, checking CVE severity, and classifying findings as still valid, changed in severity, or no longer exploitable.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/transilienceai/communitytools/regression-sweep
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 transilienceai/communitytools --skill regression-sweep
Clone the repo
git clone --depth 1 https://github.com/transilienceai/communitytools

Made for: Claude Code.

Or install communitytools, the plugin that ships this one along with the rest of its 48 skills, 5 commands, 9 agents, 1 hook.

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 regression-sweep

README.md
[![agentmods](https://agentmods.dev/badge/skills/transilienceai/communitytools/regression-sweep/github.svg)](https://agentmods.dev/skills/transilienceai/communitytools/regression-sweep)
Your own site
<a href="https://agentmods.dev/skills/transilienceai/communitytools/regression-sweep"><img src="https://agentmods.dev/badge/skills/transilienceai/communitytools/regression-sweep/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 regression-sweep

Your own site · 80×15
<a href="https://agentmods.dev/skills/transilienceai/communitytools/regression-sweep"><img src="https://agentmods.dev/badge/skills/transilienceai/communitytools/regression-sweep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,103 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00043 $0.01103
Opus 5 $0.00022 $0.00551
Sonnet 5 $0.00009 $0.00221
Haiku 4.5 $0.00004 $0.00110

Measured 9d ago against content hash 20bbecde1f71, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

regression-sweep 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 9d 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/regression-sweep/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Regression Sweep

Walk the entire validated/*.json tree, re-fire each finding's poc.py, compare output against the recorded poc_output.txt, and write a weekly drift report. Mounted onto the cloud-agent task #4.

Trigger

Cron weekly (default Mondays 02:00 UTC). May also be invoked ad-hoc after a major patch deployment.

Workflow

  1. Index validated findings. Glob validated/*.json and resolve each entry's FINDING_DIR (under findings/finding-NNN/).
  2. Per finding:
    • Re-run python3 poc.py with a 60-second timeout.
    • Capture stdout/stderr into findings/finding-NNN/evidence/validation/regression-{week}-rerun.txt.
    • Diff against findings/finding-NNN/evidence/validation/poc-rerun-output.txt (the validator's original re-run output) using a normalized line-set comparison (strip timestamps, request IDs, ephemeral tokens).
    • Re-check the finding's CVE via tools/nvd-lookup.py — has severity changed?
  3. Classify each finding into one of:
    • still_valid — re-run matches baseline within tolerance, CVSS unchanged.
    • drift_severity — re-run matches, but CVSS shifted ≥1.0 (NVD re-scored).
    • newly_invalid — re-run output diverges, exploit no longer fires. Likely patched.
    • newly_revalidated — finding had been marked REJECTED later, but now fires again. Regression.
    • inconclusive — re-run errored (network, target unreachable). Retry next sweep.
  4. Write report to artifacts/regression-{YYYYWww}.json + human-readable regression-{YYYYWww}.md. Transitions (newly_revalidated, drift_severity, newly_invalid) appear in the report under explicit headers for analyst review.

Output

{OUTPUT_DIR}/
  artifacts/
    regression-{YYYYWww}.json         # machine-readable result
    regression-{YYYYWww}.md           # human summary
  findings/finding-NNN/evidence/validation/
    regression-{YYYYWww}-rerun.txt    # captured re-run output

regression-{week}.json schema:

{
  "week": "2026W19",
  "swept_at": "2026-05-13T02:00:00Z",
  "counts": {"still_valid": 47, "drift_severity": 2, "newly_invalid": 5, "newly_revalidated": 1, "inconclusive": 3},
  "findings": [
    {"finding_id": "finding-012", "asset": "asset42", "cve": "CVE-2024-12345",
     "verdict": "newly_invalid", "reason": "PoC output diverged: response now 404",
     "baseline_cvss": 9.8, "current_cvss": 9.8}
  ]
}

Read the full file on GitHub · 68 lines

Files

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.

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. 9d ago First seen · 68 lines · 43 tokens per session scan A 20bbecde1f71

Subscribe to this mod's changes

regression-sweep is a skill published in the GitHub repository transilienceai/communitytools (515 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 1,103 once invoked, about $0.0002 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.

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