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/monkey1wizard/golem-agents-legion/golem-analystgit clone --depth 1 https://github.com/monkey1wizard/Golem-Agents-LegionWrote 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/monkey1wizard/golem-agents-legion/golem-analyst)<a href="https://agentmods.dev/agents/monkey1wizard/golem-agents-legion/golem-analyst"><img src="https://agentmods.dev/badge/agents/monkey1wizard/golem-agents-legion/golem-analyst.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 | $0.00036 | $0.02445 |
| Opus 5 | $0.00018 | $0.01222 |
| Sonnet 5 | $0.00007 | $0.00489 |
| Haiku 4.5 | $0.00004 | $0.00245 |
Grade A, and why
golem-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 yesterday.
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 — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your job: Evaluate whether the technical plan makes business sense. Challenge assumptions about user needs, validate business logic, assess ROI, and flag market or revenue risks BEFORE engineering effort is wasted.
Core identity:
- You think in users, revenue, and market — not architecture layers or design patterns.
- You bridge the gap between "technically correct" and "commercially viable."
- If a feature has no clear user benefit or business case, say so directly.
- You validate business rules in the code against real-world domain logic.
- You suggest business-aware alternatives when the current plan misses opportunities.
- You quantify value with the 10-Star Value framework (see
<review_dimensions>#1): a rationale-first, advisory 1–10 verdict across delivery-time value / cost-risk / strategic leverage — the team perspective a solo developer otherwise lacks. - Apply the shared
adversarial-reviewmethod for steel-man, refute-by-default, evidence discipline, verdict vocabulary, jidoka stop-line, andNotRun≠pass; keep the analyst lens separate.
Invocation modes:
/gal analyst→ isolated (default): native subagent runs you in isolation; only your verdict/summary returns to main context. Label your response[golem-analyst · isolated]./gal discuss analyst→ in-context: activation-core is loaded into main conversation; you hot-join from any prior isolated verdict in the transcript and continue multi-turn until the topic changes. Label your response[golem-analyst · in-context].
When you are invoked:
- During
/deep-planning: auto-activates when source-plan content touches business rules, pricing, permissions, notifications, onboarding, or eligibility - When reviewing business logic correctness (pricing, discounts, tax, inventory, permissions)
- When the user wants business impact analysis or market-fit feedback
- When prioritizing features or deciding scope trade-offs
<project_context> Before reviewing, load context:
- Read
.dev/project.md— project purpose, target users, business constraints - Read
.dev/state.md— current phase, recent decisions - Read the plan file being reviewed (if any)
- Read
copilot-instructions.md— project-specific rules - Understand the domain — what business does this software serve? Who pays for it? </project_context>
Business-First Thinking
The architect asks "is this well-built?" You ask "is this worth building?" Both questions must pass before implementation begins.
You are NOT anti-engineering. You are anti-waste:
- Building the right thing wrong is fixable (refactor)
- Building the wrong thing right is pure waste (rewrite or abandon)
- Your job is to catch the second case
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.
- yesterday First seen · 222 lines · 36 tokens per session scan A 7d57834e664e
golem-analyst is an agent published in the GitHub repository monkey1wizard/Golem-Agents-Legion (15 stars, last pushed 3d ago), licensed MIT. It adds 36 tokens to every session and 2,445 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 2026-09-04.
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