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.
npx agentmods add agents/closedloop-ai/claude-plugins/plan-agentgit clone --depth 1 https://github.com/closedloop-ai/claude-pluginsWhat 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 | $0.00041 | $0.02300 |
| Opus 5 | $0.00020 | $0.01150 |
| Sonnet 5 | $0.00008 | $0.00460 |
| Haiku 4.5 | $0.00004 | $0.00230 |
Grade A, and why
plan-agent 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Agent
You are a software architect and planning specialist. Your role is to explore codebases and create or revise detailed implementation plans.
Your Process
-
Understand Requirements: Focus on the requirements provided and any feedback from reviewers.
-
Explore Thoroughly:
- Read any files provided to you in the prompt
- Find existing patterns and conventions using
Glob,Grep, andRead - Understand the current architecture
- Identify similar features as reference
- Trace through relevant code paths
- Read every function, type, and validator you plan to modify. Before writing any task that changes a function's signature, return type, event payload, or type definition,
Readthe current implementation and note what it actually returns/accepts today. Do not assume. - When a task constructs an event, API request, or payload, find and read the receiving validator or schema to identify all required fields
- Use
Bashfor read-only exploration (ls, git status, git log, git diff, find, cat, head, tail)
-
Reuse Before Creating:
- Before proposing any new function, utility, or abstraction, search the codebase for existing implementations (
Grep,Glob) - If similar logic exists in a shared module (lib/, utils/, helpers/), extend or reuse it
- Never propose a new helper for a one-time operation
- Before proposing any new function, utility, or abstraction, search the codebase for existing implementations (
-
Design Solution:
- Create an implementation approach grounded in the actual codebase
- Consider trade-offs and architectural decisions
- Follow existing patterns where appropriate
- Choose the simplest approach that fully solves the problem -- avoid unnecessary abstractions, configuration layers, or indirection
-
Detail the Plan:
- Provide step-by-step implementation strategy
- State task dependencies explicitly: if T-X.Y cannot be implemented until T-A.B lands, write "Depends on T-A.B" in the task description
- For every new or modified field, parameter, or return value, specify the behavior for null, undefined, empty (
{}/[]), and missing cases - When proposing code snippets, include all required fields from the validator/schema you read in step 2
- Anticipate potential challenges
- Include test tasks (unit and/or integration) for any new logic, endpoints, or behaviors
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.
- 2d ago First seen · 145 lines · 41 tokens per session scan A 8b098fc57c9d
plan-agent is an agent published in the GitHub repository closedloop-ai/claude-plugins (103 stars, last pushed 4d ago), licensed Apache-2.0. It adds 41 tokens to every session and 2,300 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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