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/james-traina/compound-science/workflows-plannpx skills add James-Traina/compound-science --skill workflows-plangit clone --depth 1 https://github.com/James-Traina/compound-scienceWrote 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/james-traina/compound-science/workflows-plan)<a href="https://agentmods.dev/skills/james-traina/compound-science/workflows-plan"><img src="https://agentmods.dev/badge/skills/james-traina/compound-science/workflows-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 | $0.00017 | $0.03782 |
| Opus 5 | $0.00009 | $0.01891 |
| Sonnet 5 | $0.00003 | $0.00756 |
| Haiku 4.5 | $0.00002 | $0.00378 |
Grade A, and why
workflows:plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 489 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create an Implementation Plan for a Research Task
Pipeline mode: This command operates fully autonomously. All decisions are made automatically.
Introduction
Transform research descriptions, estimation problems, or methodological improvements into well-structured plan files that follow project conventions and best practices. This command auto-selects the appropriate detail level based on task complexity.
Research Description
<feature_description> #$ARGUMENTS </feature_description>
If the research description above is empty: Infer the task from recent context — open plan files, recent brainstorms in docs/brainstorms/, or the current estimation code. If no context is available, state "No research task provided" and stop.
0. Idea Refinement
Check for brainstorm output first:
Before analysis, look for recent brainstorm documents in docs/brainstorms/ that match this task:
ls -la docs/brainstorms/*.md 2>/dev/null | head -10
If docs/brainstorms/ does not exist, skip brainstorm lookup and proceed with task analysis.
Relevance criteria: A brainstorm is relevant if:
- The topic (from filename or YAML frontmatter) semantically matches the research description
- Created within the last 14 days
- If multiple candidates match, use the most recent one
If a relevant brainstorm exists:
- Read the brainstorm document thoroughly — every section matters
- Announce: "Found brainstorm from [date]: [topic]. Using as foundation for planning."
- Extract and carry forward ALL of the following into the plan:
- Key decisions and their rationale
- Chosen approach and why alternatives were rejected
- Constraints and requirements discovered during brainstorming
- Open questions (flag these for resolution during implementation)
- Success criteria and scope boundaries
- Any specific methodological choices or estimator selections
- Skip the idea refinement analysis below — the brainstorm already answered WHAT to do
- Use brainstorm content as the primary input to research and planning phases
- Throughout the plan, reference specific decisions with
(see brainstorm: docs/brainstorms/<filename>)when carrying forward conclusions - Do not omit brainstorm content — if the brainstorm discussed it, the plan must address it
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 · 489 lines · 17 tokens per session scan A d3c1f2dc099d
workflows:plan is a skill published in the GitHub repository James-Traina/compound-science (13 stars, last pushed 5mo ago), licensed MIT. It adds 17 tokens to every session and 3,782 once invoked, about $0.0001 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…