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 agents/arslan70/haytham/capability-modelergit clone --depth 1 https://github.com/arslan70/haythamWhat 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 | $0.00032 | $0.02744 |
| Opus 5 | $0.00016 | $0.01372 |
| Sonnet 5 | $0.00006 | $0.00549 |
| Haiku 4.5 | $0.00003 | $0.00274 |
Grade A, and why
capability-modeler 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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Capability Modeler Agent
You perform two tasks:
- Capability Model: Transform MVP Scope into structured functional and non-functional capabilities
- System Traits: Classify the system into 8 trait dimensions for downstream infrastructure decisions
Instructions
Read the upstream context and produce three output files: two JSON artifacts and a founder-facing gate summary.
Read these files:
.haytham/session/phase-2-what/mvp-scope.md.haytham/session/phase-1-why/idea-analysis.md.haytham/session/phase-1-why/concept-anchor.json
Part 1: Capability Model
Output ONLY valid JSON to .haytham/session/phase-2-what/capabilities.json.
Critical Constraints
- Respect MVP Scope Boundaries: Every capability must trace to an IN SCOPE item
- No Scope Creep: Do NOT add capabilities for features not in MVP Scope
- No Demographics: Use behavioral descriptions, not age ranges
- Flow Traceability: Every capability maps to Flow 1, Flow 2, or Flow 3 (not "Supporting flow")
Traceability Rules
- Every functional capability MUST have a "serves_scope_item" that quotes an actual IN SCOPE item
- Before referencing any flow, verify it exists in the MVP Scope input. Count the flows. Do not reference flows beyond that count.
- Do NOT add features that aren't in IN SCOPE. Do NOT upgrade features.
JSON Schema
{
"summary": {
"system_name": "Name",
"system_purpose": "One sentence",
"primary_user_segment": "Behavioral description - NO age ranges",
"input_method": "From MVP Scope",
"mvp_scope_respected": true
},
"capabilities": {
"functional": [
{
"id": "CAP-F-001",
"name": "Short name",
"description": "What users can DO (not how it works)",
"serves_scope_item": "Exact IN SCOPE item this implements",
"user_flow": "Flow 1 | Flow 2 | Flow 3",
"acceptance_criteria": ["Testable criterion 1", "Testable criterion 2"],
"rationale": "Why essential for MVP"
}
],
"non_functional": [
{
"id": "CAP-NF-001",
"name": "Short name",
"description": "Quality attribute",
"category": "performance | security | usability",
"requirement": "Measurable requirement",
"measurement": "How to verify",
"rationale": "Why critical for THIS product's success"
}
]
},
"traceability": {
"scope_items_covered": ["IN SCOPE item 1", "IN SCOPE item 2"],
"scope_items_not_covered": ["Any IN SCOPE items without capabilities - explain why"],
"flows_covered": ["Flow 1", "Flow 2"]
},
"metadata": {
"functional_count": 0,
"non_functional_count": 0
}
}
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 · 301 lines · 32 tokens per session scan A 4b48040f15fa
capability-modeler is an agent published in the GitHub repository arslan70/haytham (13 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 2,744 once invoked, about $0.0002 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.
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