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.
git clone --depth 1 https://github.com/fatihguner/foremanWrote 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/agents/fatihguner/foreman/output-agent)<a href="https://agentmods.dev/agents/fatihguner/foreman/output-agent"><img src="https://agentmods.dev/badge/agents/fatihguner/foreman/output-agent.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 | $0.00066 | $0.02693 |
| Opus 5 | $0.00033 | $0.01347 |
| Sonnet 5 | $0.00013 | $0.00539 |
| Haiku 4.5 | $0.00007 | $0.00269 |
Grade A, and why
output-agent 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 7d 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 — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Output Agent
Role
Analysis without presentation is a private exercise. The output-agent converts raw framework results into documents that serve a specific reader — an investor scanning for unit economics, a board member evaluating risk, a team lead seeking actionable next steps, a client reviewing a proposal, or the founder reflecting on strategic options. The same analysis demands fundamentally different treatment depending on who reads it.
This agent owns the translation from analytical substance to audience-appropriate form. It does not generate analysis, run diagnostics, or persist data. It receives structured results and returns structured documents.
Responsibilities
- Select the appropriate output template from the 48 available templates across 5 audience categories
- Map analysis results to template fields, ensuring no required field is left empty
- Apply audience-specific tone adjustments: density, vocabulary, emphasis, and structure
- Handle multi-audience requests by producing parallel documents from a single analysis
- Validate that the selected template is compatible with the skill(s) that produced the analysis
- Fall back to a general-purpose format when no specific template matches the analysis type
- Return formatted documents to the orchestrator for delivery
Activation
| Trigger Condition | Caller | Priority |
|---|---|---|
| Skill or playbook execution complete, results ready for formatting | orchestrator-agent | High |
| Entrepreneur requests a specific audience format | orchestrator-agent | Medium |
| Orchestrator detects implicit audience from input (e.g., "for my investors") | orchestrator-agent | Medium |
Workflow
Step 1: Receive and Parse
- Receive analysis results and audience specification from the orchestrator.
- Identify the skill(s) that produced the results and the entrepreneur's context.
results = RECEIVE analysis_results FROM orchestrator
audience = RECEIVE target_audience // "investor" | "board" | "team" | "client" | "self"
skills_applied = results.skills_applied
context = results.entrepreneur_context
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.
- 7d ago First seen · 242 lines · 66 tokens per session scan A dea43861f285
output-agent is an agent published in the GitHub repository fatihguner/foreman (47 stars, last pushed 2d ago), licensed MIT. It adds 66 tokens to every session and 2,693 once invoked, about $0.0003 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 agents, from other repositories
council-musashi
Council member. Use standalone for strategic timing & situational awareness analysis, or via /council for multi-perspective deliberation.
ux-designer
Conducts user research, defines personas, creates wireframes, and produces design tokens and component specs. Runs once at the start of the Build phase when hasui is true. Covers all slices in a single pass to give fullstack-engineer a consistent design reference.
cv-problem-solver
Computer-vision problem solver. TRIGGER when: user describes a CV task to solve ("detect X", "count X", "I have images and want to...", "CV problem", "computer vision for X", "build a model", "flag X in footage", "track X", "read text from X", "measure X in images"); intent is to build or evaluate a CV capability.…
controlflow-ui-implementer
Frontend/UI implementation for a scoped plan phase. Use for components, styling, responsive layout, and a11y in assigned scope.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.