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 ai-ecoverse/slicc --skill workflowsgit clone --depth 1 https://github.com/ai-ecoverse/sliccWrote 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/ai-ecoverse/slicc/workflows)<a href="https://agentmods.dev/skills/ai-ecoverse/slicc/workflows"><img src="https://agentmods.dev/badge/skills/ai-ecoverse/slicc/workflows.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 5.1 | $0.00111 | $0.01228 |
| Opus 5 | $0.00056 | $0.00614 |
| Sonnet 5 | $0.00022 | $0.00246 |
| Haiku 4.5 | $0.00011 | $0.00123 |
Grade A, and why
workflows 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflows
A workflow is a plain-JS orchestration script that fans out to parallel sub-agents and
keeps intermediate results in script variables (not your context). You author it, run it
with workflow run, and — once it's good — workflow save it as a reusable command.
When to reach for a workflow
- A sweep over many files/items where each unit is independent (lint, classify, summarize).
- A migration applied across a codebase in parallel, then aggregated.
- Research that fans out to several sources and cross-checks them.
- Multi-angle planning (draft N approaches in parallel, then synthesize).
If it's a single self-contained task, just use a plain scoop or the agent command — a
workflow is overhead you don't need.
The API (available inside a workflow script)
agent(prompt, opts?)→ the sub-agent's text (or parsed JSON whenopts.schemais set), ornullon failure.opts:{ model?, thinking?, schema?, phase?, label? }.model: a bare model id (runmodelsto see the ids you can use) to run this sub-agent on a specific model; omit to inherit the workflow's model. Always pass the bare id (e.g.claude-opus-4-8), never aprovider:modelform.thinking:off | minimal | low | medium | high | xhigh(per-agent reasoning effort).schema: a JSON Schema; the result is constrained to it and JSON-parsed for you.phase/label: display-only grouping (no execution effect yet).
parallel(thunks)→ runs an array of() => Promiseconcurrently (bounded by the cap).pipeline(items, ...stages)→ maps items through stages.phase(title)/log(message)→ progress markers.args→ the value passed when the workflow is invoked (<name> '<json>').
Authoring
A workflow MUST export a meta block with a name (description optional):
export const meta = { name: 'weekly-audit', description: 'Audit each package in parallel' };
const pkgs = args?.packages ?? ['webapp', 'node-server'];
phase('audit');
const findings = await parallel(
pkgs.map((p) => () => agent(`Audit packages/${p} for TODOs. One line each.`, { thinking: 'low' }))
);
return findings.filter(Boolean);
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 · 99 lines · 111 tokens per session scan A 3220a0f91c79
workflows is a skill published in the GitHub repository ai-ecoverse/slicc (30 stars, last pushed today), licensed Apache-2.0. It adds 111 tokens to every session and 1,228 once invoked, about $0.0006 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 2026-09-05.
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