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 skills add Tarekkharsa/agentstack --skill propose-workflowgit clone --depth 1 https://github.com/Tarekkharsa/agentstackWrote 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/tarekkharsa/agentstack/propose-workflow)<a href="https://agentmods.dev/skills/tarekkharsa/agentstack/propose-workflow"><img src="https://agentmods.dev/badge/skills/tarekkharsa/agentstack/propose-workflow/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.
<a href="https://agentmods.dev/skills/tarekkharsa/agentstack/propose-workflow"><img src="https://agentmods.dev/badge/skills/tarekkharsa/agentstack/propose-workflow.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00075 | $0.04499 |
| Opus 5.5 | $0.00030 | $0.01800 |
| Sonnet 5.5 | $0.00015 | $0.00900 |
| Haiku 4.5 | $0.00007 | $0.00450 |
Grade A, and why
propose-workflow 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 1mo 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 — 349 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Propose a reviewable workflow
Use when the user wants to design or build a workflow and review it before it runs — "let's design a workflow for X", "build me a workflow but let me see it first", "what shape would you use for X". You emit a blueprint (the shape: pattern, phases, per-node role/model/effort/instruction, symbolic fan-out, edges), the panel draws it as a graph, and the user approves / rejects / edits. Only on approve do you author and run it.
The judgment worth reviewing is which algorithm you chose — fan-out map→reduce for "audit this repo" vs a judge panel for "design an API". Emit the shape; let the human check it.
1 — Propose, or just run?
Mode is the user's intent, not a setting — infer it:
- "Just run a workflow" / "go" / "do X across the files" → skip this gate.
Author and run it the normal way — the declare → lock → trust →
agentstack workflow runpipeline in §4. Same pipeline, gate auto-skips. - "Design / build / let me review / show me the shape first" → propose a blueprint (below), then stop and wait. Do not author, do not run.
When unsure which the user meant, propose — a review gate is cheap to approve and expensive to skip.
2 — Emit the blueprint, then stop
Pick the best-fitting pattern for the task and name it. One node per
role/step; give each a model/effort/instruction; edges carry a kind.
Emit it in a fenced block whose language tag is exactly
agentstack-blueprint — that tag is how the panel intercepts and renders it.
```agentstack-blueprint
{
"workflow": "repo-audit",
"pattern": "map-reduce",
"goal": "Find and rank bugs across the changed files",
"nodes": [
{ "id": "map", "phase": "Find", "role": "reviewer",
"model": "gpt-5.5", "effort": "low",
"instruction": "Scan ONE changed file for correctness bugs",
"fanout": "1 per changed file" },
{ "id": "reduce", "phase": "Rank", "role": "synthesizer",
"model": "opus", "effort": "high",
"instruction": "Dedupe and rank all findings by severity",
"fanout": null }
],
"edges": [ { "from": "map", "to": "reduce", "kind": "fan-in" } ]
}
```
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.
- 1mo ago First seen · 349 lines · 75 tokens per session scan A 05960342eade
propose-workflow is a skill published in the GitHub repository Tarekkharsa/agentstack (3 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 75 tokens to every session and 4,499 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
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