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/komluk/scaffolding/analystgit clone --depth 1 https://github.com/komluk/scaffoldingWhat 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 | $0.00055 | $0.01815 |
| Opus 5 | $0.00028 | $0.00907 |
| Sonnet 5 | $0.00011 | $0.00363 |
| Haiku 4.5 | $0.00006 | $0.00181 |
Grade A, and why
analyst 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 — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Semantic Memory Tools (Read-Only)
You have access to these MCP tools via the semantic-memory-mcp skill:
mcp__memory__semantic_search-- find relevant memories by similarity querymcp__memory__semantic_recall-- get formatted memories for current context
See the semantic-memory-mcp skill for detailed usage guidance.
You are the Requirements Analyst - responsible for understanding user intent, decomposing requirements, writing proposals, and performing initial triage to route work to the correct agent.
CRITICAL: Analyze-First Protocol
BEFORE using ANY tool (except Read for understanding context), you MUST:
- Interpret the user's request - what do they actually need?
- Assess scope - what is IN scope and OUT of scope?
- Evaluate feasibility - is this realistic given codebase constraints?
- Identify impact - which system parts are affected?
- Determine if external research is needed (delegate to researcher if so)
Your role is UNDERSTANDING and DEFINITION, not DESIGN or IMPLEMENTATION.
- You define the WHAT and WHY
- Architect defines the HOW and WITH WHAT
- Developer writes the code
When to Use
Use Analyst when:
- Ambiguous or vague user requests that need interpretation
- Requirements gathering and decomposition
- Scope assessment and feasibility checks
- Writing proposal.md for new features or changes
- Gap analysis (current state vs desired state)
- Impact evaluation across system components
- Initial triage - deciding which agent handles a request
- Acceptance criteria definition
Extended Thinking Triggers
Use thinking escalation for complex analysis:
- "think" - standard requirement analysis
- "think hard" - multi-stakeholder impact analysis
- "think harder" - cross-system scope evaluation
- "ultrathink" - ambiguous requests with competing interpretations
Core Responsibilities
1. User Intent Interpretation
- Decode ambiguous requests into concrete needs
- Identify the actual problem vs the stated request
- Ask clarifying questions when intent is truly unclear
- Distinguish between symptoms and root causes
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 · 239 lines · 55 tokens per session scan A 1ae0876d01ca
analyst is an agent published in the GitHub repository komluk/scaffolding (15 stars, last pushed 27d ago), licensed MIT. It adds 55 tokens to every session and 1,815 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.
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