big-work-plan-review

big-work-plan-review is a skill for Claude Code from andr-ca/agentharness. It costs 80 tokens per session (1,555 once invoked), scanned A, original, MIT.

A planning review for large, stateful, or concurrent software projects. It has two independent AI reviewers examine a written implementation plan in several rounds before coding begins.

In plain words
What is it for?
Use it before building new systems, pipelines, background services, or software with multiple writers, ordering rules, or long-lived state.
Why use it?
It helps catch expensive design mistakes before they become code, such as data loss, blocked processing, or corrupted shared state.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions subagents.

Good fit Use it before building new systems, pipelines, background services, or software with multiple writers, ordering rules, or long-lived state.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/andr-ca/agentharness/big-work-plan-review
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 andr-ca/agentharness --skill big-work-plan-review
Clone the repo
git clone --depth 1 https://github.com/andr-ca/agentharness

Made for: Claude Code.

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 big-work-plan-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/andr-ca/agentharness/big-work-plan-review.svg)](https://agentmods.dev/skills/andr-ca/agentharness/big-work-plan-review)
Your own site
<a href="https://agentmods.dev/skills/andr-ca/agentharness/big-work-plan-review"><img src="https://agentmods.dev/badge/skills/andr-ca/agentharness/big-work-plan-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,555 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 $0.00080 $0.01555
Opus 5 $0.00040 $0.00777
Sonnet 5 $0.00016 $0.00311
Haiku 4.5 $0.00008 $0.00155

Measured 7d ago against content hash e36b375e0803, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

big-work-plan-review 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 7d 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.

.claude/skills/big-work-plan-review/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Big-Work Adversarial Plan Review

Ported from a workflow validated on a real design (an ntfy ingestion + persona memory pipeline) that went from roughly 3.5/10 to roughly 8.5/10 across 4 review rounds — each round finding genuine production-breaking defects a single author missed: processed-before-persisted data loss, an LLM call blocking a shared stream thread, mutable-JSONL status corruption, an answer-handling path that let contradiction answers poison an importance-rule store, and free-text LLM writes into what should have been a structured graph.

This is a from-description port. It was written from a GitHub issue proposal, not from the original Cursor-format draft it references (~/.cursor/skills/big-work-plan-review/SKILL.md, on the proposing operator's own machine) — that draft was unreachable from the session that built this file. Reconcile against the original draft if it surfaces later; treat this version as functionally complete in the meantime, not as a placeholder.

When to use this

Big, stateful, or concurrent work: new systems, pipelines, daemons, anything with multiple writers, ordering dependencies, or state that outlives a single request. The cost of a design mistake here is a production incident, not a failed test.

When NOT to use this: a scoped bug fix with one clear resolution, a single-file change, or anything requirements-clarification already covers by itself. Running a two-reviewer adversarial loop on a small change is pure overhead — match the ceremony to the blast radius.

The loop

  1. Research verified facts, not assumptions. Probe the live systems this design touches — actual schemas, actual message shapes, actual failure behavior — before writing a line of the plan. Record findings in a "Current state (verified)" section so a reviewer can tell what you checked from what you assumed.

  2. Write the plan. One doc in docs/plans/, with these sections at minimum:

    • Goal
    • Current state (verified)
    • Architecture
    • Exact schemas / DDL / message contracts
    • Module contracts (inputs, outputs, invariants each module owns)
    • Failure-modes table (what breaks, how it's detected, what happens next)
    • Testing approach
    • Out of scope

Read the full file on GitHub · 141 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. 7d ago First seen · 141 lines · 80 tokens per session scan A e36b375e0803

Subscribe to this mod's changes

big-work-plan-review is a skill published in the GitHub repository andr-ca/agentharness (1 stars, last pushed today), licensed MIT. It adds 80 tokens to every session and 1,555 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.

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