A structured planning and review workflow for significant code changes. It examines architecture, code quality, tests, and performance, with interactive questions before continuing.

Planning a large or small engineering change and reviewing its system design, code organisation, tests, performance, and security boundaries.

It helps identify design, testing, security, coupling, and scaling concerns before implementation begins.

How dfridkin/clawops configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to dfridkin/clawops. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/dfridkin/clawops/main/.claude/skills/plan/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/dfridkin/clawops

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/dfridkin/clawops/plan/github.svg)](https://agentmods.dev/skills/dfridkin/clawops/plan)

Your own site

<a href="https://agentmods.dev/skills/dfridkin/clawops/plan"><img src="https://agentmods.dev/badge/skills/dfridkin/clawops/plan/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/dfridkin/clawops/plan"><img src="https://agentmods.dev/badge/skills/dfridkin/clawops/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 529 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.

Model	Per session	Once invoked
Fable 5.1	$0.00000	$0.00529
Opus 5.5	$0.00000	$0.00212
Sonnet 5.5	$0.00000	$0.00106
Haiku 4.5	$0.00000	$0.00053

Measured 2mo ago against content hash dacc764f28a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

plan 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 2mo 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/plan/SKILL.md · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/plan

Structured planning and review workflow. Use before making significant code changes.

Engineering preferences (apply throughout)

DRY — flag repetition aggressively.
Well-tested — more tests rather than fewer; non-negotiable.
Engineered enough — not fragile/hacky, not prematurely abstracted.
Edge cases — thoughtfulness over speed; handle more, not fewer.
Explicit over clever — always.

Before starting

Ask the user which mode they want:

1 / BIG CHANGE — Work through all four sections interactively (Architecture → Code Quality → Tests → Performance), with at most 4 top issues per section. Pause for feedback after each section before moving on.

2 / SMALL CHANGE — Work through interactively with ONE question per section.

Review sections

1. Architecture review

Evaluate:

Overall system design and component boundaries.
Dependency graph and coupling concerns.
Data flow patterns and potential bottlenecks.
Scaling characteristics and single points of failure.
Security architecture (auth, data access, API boundaries).

2. Code quality review

Evaluate:

Code organisation and module structure.
DRY violations — be aggressive.
Error handling patterns and missing edge cases (call these out explicitly).
Technical debt hotspots.
Areas that are over-engineered or under-engineered.

3. Test review

Evaluate:

Test coverage gaps (unit, integration, e2e).
Test quality and assertion strength.
Missing edge case coverage.
Untested failure modes and error paths.

4. Performance review

Evaluate:

N+1 queries and data access patterns.
Memory-usage concerns.
Caching opportunities.
Slow or high-complexity code paths.

Format for every issue found

For each specific issue (bug, smell, design concern, or risk):

Describe the problem concretely, with file and line references.
Present 2–3 options, including "do nothing" where reasonable.
For each option specify: implementation effort, risk, impact on other code, maintenance burden.
Give an opinionated recommendation mapped to the engineering preferences above. Always list the recommended option first.
Use AskUserQuestion — number each issue and letter each option (e.g. Issue 3, Option A) so the user can respond unambiguously.

Read the full file on GitHub · 76 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.

2mo ago First seen · 76 lines · 0 tokens per session scan A dacc764f28a1

Subscribe to this mod's changes

plan is a skill published in the GitHub repository dfridkin/clawops (6 stars, last pushed today), licensed MPL-2.0. It costs nothing until one of its globs matches a file; then it loads 529 tokens. 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.

Planning agent-infrastructure ai-agents aws azure claude cli

plan next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
plandfridkin/clawops	Skill	6	today	MPL-2.0	A	0	Claude Code
aws-clielasticdotventures/_b00t_	Skill	15	12d ago	none	A	31	Claude Code
notionArvo-AI/aurora	Skill	454	yesterday	Apache-2.0	A	23	Claude Code
aws-essentialsericrisco/rsc-harness	Skill	503	2d ago	MIT	A	89	Claude Code, Codex
dynamodbericrisco/rsc-harness	Skill	503	2d ago	MIT	A	82	Claude Code, Codex
datadogArvo-AI/aurora	Skill	454	yesterday	Apache-2.0	A	28	Claude Code
scalewayArvo-AI/aurora	Skill	454	yesterday	Apache-2.0	A	29	Claude Code

clawops: Skill for Claude Code

Borrowing it

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

/plan

Engineering preferences (apply throughout)

Before starting

Review sections

1. Architecture review

2. Code quality review

3. Test review

4. Performance review

Format for every issue found

What this file has done since we first saw it

plan compared with skills from other repositories