running-review-recovery

running-review-recovery is a skill for Claude Code from danielkinneyspears/federal-proposal-skills. It costs 77 tokens per session (1,418 once invoked), scanned A, original, Apache-2.0.

A proposal follow-up process that turns findings from a Pink, Red, or Gold Team review into assigned fixes and verified closures. These are stages of review used to find weaknesses in a government bid.

In plain words
What is it for?
Use it to assign findings, track their closure, check changes against the solicitation and compliance matrix, and report remaining work.
Why use it?
It prevents review findings from being recorded without actually correcting the proposal before the next deadline.

Skill for Claude Code

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

Part of the federal-proposal-skills plugin — 22 skills shipped together

Good fit Use it to assign findings, track their closure, check changes against the solicitation and compliance matrix, and report remaining work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/danielkinneyspears/federal-proposal-skills/running-review-recovery
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 danielkinneyspears/federal-proposal-skills --skill running-review-recovery
Clone the repo
git clone --depth 1 https://github.com/danielkinneyspears/federal-proposal-skills

Made for: Claude Code.

Or install federal-proposal-skills, the plugin that ships this one along with the rest of its 22 skills.

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 running-review-recovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/danielkinneyspears/federal-proposal-skills/running-review-recovery/github.svg)](https://agentmods.dev/skills/danielkinneyspears/federal-proposal-skills/running-review-recovery)
Your own site
<a href="https://agentmods.dev/skills/danielkinneyspears/federal-proposal-skills/running-review-recovery"><img src="https://agentmods.dev/badge/skills/danielkinneyspears/federal-proposal-skills/running-review-recovery/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 running-review-recovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/danielkinneyspears/federal-proposal-skills/running-review-recovery"><img src="https://agentmods.dev/badge/skills/danielkinneyspears/federal-proposal-skills/running-review-recovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,418 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 $0.00077 $0.01418
Opus 5 $0.00039 $0.00709
Sonnet 5 $0.00015 $0.00284
Haiku 4.5 $0.00008 $0.00142

Measured 12d ago against content hash 3ad659340a8f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

running-review-recovery 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 12d 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/running-review-recovery/SKILL.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Running Review Recovery

Turn review findings into fixed proposal. A color team review produces a findings matrix; recovery is the disciplined work of closing every finding that matters before the next milestone. A Red Team without recovery is theater — the weaknesses were found and then shipped anyway. This skill owns the recovery process: assign each finding, drive the rewrites, verify each fix against the standard, and report a burn-down the team can trust.

When to use this skill

Use this skill immediately after a color team review (reviewing-color-teams), in the recovery window the schedule reserves. Run it after a Pink, Red, or Gold review — any review that produced findings to work.

It does not perform the reviews (reviewing-color-teams) and does not write proposal content (the drafting skills). It manages the closure of findings and verifies it.

Inputs

Required:

  • The color review artifact (20-color-review-<team>.md) with its findings matrix.
  • 10-compliance-matrix.md: the standard each fix is verified against.
  • The proposal content the findings point to — 12-sections/ and the volume artifacts.

Preferred upstream artifacts:

  • The solicitation Section M — the scoring standard the fixes must satisfy.
  • 09-proposal-management/: the schedule, so recovery fits the window, and the action register, which recovery actions feed into.

Read ../../shared/glossary.md and ../../shared/pursuit-workspace.md if not already read this session.

Intake

Ask these as a numbered list.

  1. Which review. Which color review's findings is this recovery working, and where is the findings matrix?
  2. The recovery window. How much time is there before the next milestone (the next review, or submission)?
  3. The team. Who is available to make the fixes — the section authors, volume leads?
  4. Scope. Recover all findings, or a defined subset (for example, deficiencies and significant weaknesses only, given a short window)?

Read the full file on GitHub · 135 lines

Files

What ships with it

2 files 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. 12d ago First seen · 135 lines · 77 tokens per session scan A 3ad659340a8f

Subscribe to this mod's changes

running-review-recovery is a skill published in the GitHub repository danielkinneyspears/federal-proposal-skills (5 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 77 tokens to every session and 1,418 once invoked, about $0.0004 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 2026-08-31.

Related

Other skills, from other repositories

analyzing-competitors

Produces a Black Hat competitive assessment for a US Federal opportunity as a wiki of competitor entities. Use when the user needs competitive analysis, a Black Hat review or session, competitor profiling, an incumbent assessment, or to understand the competitive field for a federal bid. Creates and enriches one…

danielkinneyspears/govcon-pursuit-brain · 108 tokens

qualifying-opportunities

Runs a structured bid/no-bid gate review for a US Federal opportunity and bootstraps the pursuit's knowledge wiki. Use when deciding whether to pursue or bid a federal solicitation, RFP, RFQ, RFI, sources-sought notice, or IDIQ task order — for a bid/no-bid decision, pursuit decision, gate review, opportunity…

danielkinneyspears/govcon-pursuit-brain · 115 tokens

igce-builder-ffp

Trigger for: FFP IGCE, firm-fixed-price estimate, FFP cost model, proposed FFP rate validation, wrap-rate analysis, Agency BPA rate comparison, price-reasonableness memo, or fair-and-reasonable analysis. Build auditable Firm-Fixed-Price federal estimates using BLS OEWS wages, layered fringe/overhead/G&A/profit, GSA…

1102tools-dev/federal-contracting-skills · 188 tokens

market-research-workflow

Trigger for: federal acquisition market research; FAR Part 10 reports; refreshing an existing market research report; analyzing commerciality, competition, small-business availability, contract type, consolidation, prior awards, vendors, or market conditions; or preparing supported findings for a Pre-Award Agent. A…

1102tools-dev/federal-contracting-skills · 159 tokens

acquisition-policy-workflow

Trigger for: explaining current FAR, DFARS, or agency-supplement text; determining documented acquisition-policy status for an agency and FAR part; comparing codified text, RFO model text, and agency deviations; tracing acquisition rulemaking; finding procurement comment periods; analyzing public comments; refreshing…

1102tools-dev/federal-contracting-skills · 115 tokens

govcon-growth-workflow

Trigger for: finding federal opportunities; capture and bid screening; competitor or incumbent intelligence; recompete pipelines; teaming partner research; agency, customer, or market intelligence; federal labor-rate or pricing context; or refreshing prior GovCon research. Always begin with the local SAM.gov…

1102tools-dev/federal-contracting-skills · 115 tokens