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 skills/codagent-ai/agent-skills/simple-plannpx skills add Codagent-AI/agent-skills --skill simple-plangit clone --depth 1 https://github.com/Codagent-AI/agent-skillsWrote 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.
[](https://agentmods.dev/skills/codagent-ai/agent-skills/simple-plan)<a href="https://agentmods.dev/skills/codagent-ai/agent-skills/simple-plan"><img src="https://agentmods.dev/badge/skills/codagent-ai/agent-skills/simple-plan.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00077 | $0.00763 |
| Opus 5 | $0.00039 | $0.00381 |
| Sonnet 5 | $0.00015 | $0.00153 |
| Haiku 4.5 | $0.00008 | $0.00076 |
Grade A, and why
simple-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 4d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Simple Plan
Plan a small change in one focused conversation. Produce a concise proposal.md, one spec per
capability, an optional design.md, and a tasks.md handoff. The artifacts must be self-contained for
an implementing agent with no conversation history.
Process
- Understand the problem, desired behavior, success criteria, and scope. Lightly inspect related specifications and relevant code so questions and artifacts reflect the existing system.
- Use
codagent:ask-questionsto resolve only material behavior, boundaries, errors, edge cases, and scope. Recommend defaults and decide ordinary implementation details from context. - Decide whether
design.mdis necessary. Default to no; write one only for a consequential architectural choice, non-obvious rationale, migration, integration strategy, or implementation constraint that the implementer otherwise would not know. - Present the proposed capability set, design-doc decision, output location, and consequential assumptions for user approval.
- Write all artifacts in one pass, then check them together for missing decisions or contradictions.
Follow a project-defined location. Otherwise propose
~/.agent-skills/changes/<kebab-slug>/ and confirm it before writing. Do not turn this into the full
propose/spec/design ceremony or write a detailed task breakdown.
Artifact requirements
proposal.md
Keep the proposal brief: why, high-level changes, new and modified capabilities, out of scope, and impact.
## Why
<problem or opportunity>
## What Changes
- <high-level change>
## Capabilities
### New Capabilities
- `<name>`: <brief description>
### Modified Capabilities
- `<existing-name>`: <changed requirements>
## Out of Scope
<explicit exclusions>
## Impact
<affected code, APIs, dependencies, or users>
specs/<capability>/spec.md
Specifications are the load-bearing artifact. Use SHALL or MUST, observable behavior, and at least one
#### Scenario: with WHEN/THEN per requirement. For a modified requirement, copy the complete existing
requirement and all scenarios under ## MODIFIED Requirements before editing it. If behavior truly
depends on an unresolved architectural choice, mark the scenario
<!-- deferred-to-design: <reason> --> and resolve it in the design.
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.
- 4d ago First seen · 99 lines · 77 tokens per session scan A bf4379d79d3d
simple-plan is a skill published in the GitHub repository Codagent-AI/agent-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 763 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…