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/sjarmak/agent-workflows/composenpx skills add sjarmak/agent-workflows --skill composegit clone --depth 1 https://github.com/sjarmak/agent-workflowsWhat 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 | $0.00000 | $0.02673 |
| Opus 5 | $0.00000 | $0.01337 |
| Sonnet 5 | $0.00000 | $0.00535 |
| Haiku 4.5 | $0.00000 | $0.00267 |
Grade A, and why
compose 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 — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Pipeline Builder. A meta-workflow that takes a goal and designs which existing workflow skills to chain together, in what order, with what parameters. Spawns agents to independently propose different workflow compositions for the same goal. The only workflow that operates on the WORKFLOW LAYER rather than the problem layer. Produces a recommended pipeline with rationale.
Arguments
$ARGUMENTS — format: [N] "goal description" where N is optional pipeline-proposal count (default: 3, min 2, max 5)
Parse Arguments
Extract:
- agent_count: the optional leading integer (default 3, min 2, max 5)
- goal: the quoted or unquoted goal description — what the user wants to achieve end-to-end
If the goal is missing or unclear, ask the user to clarify before proceeding.
Phase 1: Analyze the Goal
Before spawning agents, classify the goal along five dimensions. For each dimension, assign a rating and a one-sentence justification:
| Dimension | Rating | Justification |
|---|---|---|
| Novelty | Low / Medium / High | How much prior art exists for this kind of problem? |
| Urgency | Low / Medium / High | How time-sensitive is delivery? |
| Risk Level | Low / Medium / High | What is the blast radius if the solution is wrong? |
| Team Size | Solo / Small (2-4) / Large (5+) | How many people will execute? |
| Reversibility | Easy / Moderate / Hard | How costly is it to undo decisions made during implementation? |
Prepare a goal analysis brief that includes:
- The goal restated in one sentence
- The dimension ratings table above
- Key constraints or context from the conversation
- What "done" looks like for this goal
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 · 231 lines · 0 tokens per session scan A 96f51b440b33
compose is a skill published in the GitHub repository sjarmak/agent-workflows (9 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,673 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.
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