Business idea evaluator
Skill 2612evgenii-hue/business-idea-evaluator/business-idea-evaluator
Объективная оценка бизнес-идей через 18 субагентов и Business Reality Score. Agent Skill для Claude Code, Cursor и Codex.
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Objectively evaluates business ideas through 18 independent subagents, evidence grading, probabilistic modeling, and Business Reality Score (BRS). Use when the user asks to evaluate, validate, score, or stress-test a business idea, startup concept, side project, SaaS idea, or monetization plan. Always use for business idea analysis — never evaluate from gut feeling in main context. Requires real subagent invocation, not simulated expert opinions.
SKILL.md
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Business Idea Evaluator
Professional analytical system. Not a motivational coach. Evaluate the idea, not the user's enthusiasm.
Non-negotiable rules
- Never evaluate before idea is confirmed — complete Phase 1 first.
- Never simulate subagents in main context — launch all 18 via Task/Agent tool.
- Never use simple arithmetic mean for final score — use
scripts/calculate_brs.py. - Never flatter — see references/forbidden-phrases.md.
- Never claim "no competitors" without expert 01 completing deep search.
- Mark evidence status on every material claim — see references/evidence-status.md.
- If web search unavailable, state it once and downgrade all market claims to hypotheses.
Pre-flight — verify subagents before Phase 2
Mandatory. Before launching any subagent, run from project root:
bash .agents/skills/business-idea-evaluator/scripts/verify_subagents.sh
If verification fails, install and re-verify:
bash .agents/skills/business-idea-evaluator/scripts/install-agents.sh
Do not proceed to Phase 2 until .cursor/agents/, .claude/agents/, .agents/agents/, and .codex/agents/ each contain all 18 subagents. First-time setup: bash .agents/skills/business-idea-evaluator/scripts/bootstrap.sh
Anti-simulation gate (Phases 2–3)
These actions are forbidden in the main agent context:
- Writing expert or math JSON without a completed Task/Agent invocation for that agent
- Summarizing what an expert "would say" instead of launching the subagent
- Skipping failed agents without
failed_agentsentry and retry
Required: 12 + 6 = 18 separate Task/Agent invocations, each with subagent_type matching the agent name (e.g. biz-eval-01-analog-research). Launch all agents in a phase within one message (parallel).
After each phase, briefly confirm: «Запущено N/N субагентов, получено N/N JSON-ответов» before proceeding.
Phase 1 — Idea discovery (5 questions)
See references/discovery-protocol.md for slot map and examples.
Ask exactly one question per message. Wait for answer before next question.
| # | Goal | First question depends on |
|---|---|---|
| 1 | Who is the paying customer | Your reading of user's initial idea |
| 2 | Specific pain + frequency | Answer to Q1 |
| 3 | Current workaround + cost of pain | Answer to Q2 |
| 4 | Product format + what customer pays for | Answer to Q3 |
| 5 | Launch market + MVP constraints | Answer to Q4 |
Rules for questions:
- Max 2 sentences per question.
- No "tell me more" or open-ended prompts.
- Each question must extract one concrete business-model element.
- Track answers internally; do not dump full Q&A into final report.
After Q5, output only:
Я понял идею так: [one dense paragraph covering: audience, pain, solution,
delivery format, monetization, launch market, differentiation, first MVP]
Then ask: «Подтверждаешь такую формулировку или нужно поправить?»
- If user corrects → update paragraph, ask confirmation again.
- Do not proceed to Phase 2 until explicit confirmation («да», «подтверждаю», «верно», etc.).
Save confirmed idea as IDEA_BRIEF for all subagents.
Phase 2 — Expert layer (12 subagents)
Launch all 12 in parallel (one message, 12 Task/Agent invocations). Read references/expert-evidence-package.md for output schema.
| Agent file | Role |
|---|---|
biz-eval-01-analog-research | Deep analog & substitute search |
biz-eval-02-pain-demand | Real pain & willingness to pay |
biz-eval-03-audience-behavior | Buyer behavior & acquisition |
biz-eval-04-market-country | Country/market realities |
biz-eval-05-trends-longevity | Trend & 1–5y durability |
biz-eval-06-monetization | Revenue model & unit economics hints |
biz-eval-07-marketing | Channels & trust barriers |
biz-eval-08-implementation | MVP & technical feasibility |
biz-eval-09-legal-platform | Legal/platform/ethical risks |
biz-eval-10-competitive-moat | Copyability & defensibility |
biz-eval-11-launch-zero | 7/30/90 day launch plan |
biz-eval-12-red-team | Attack the idea |
Install agents if missing: run bash .agents/skills/business-idea-evaluator/scripts/install-agents.sh from project root.
Cursor / Claude — Task invocation pattern
One message, 12 parallel Task calls. Example for expert 01:
subagent_type: biz-eval-01-analog-research
prompt: |
IDEA_BRIEF:
<confirmed paragraph>
TASK: Execute your role per agent definition. Use web search if available.
Return ONLY valid JSON matching the schema in
.agents/skills/business-idea-evaluator/references/expert-evidence-package.md
for agent_id "01". Include sources with URLs when found.
Repeat for biz-eval-02-pain-demand … biz-eval-12-red-team in the same message.
Codex — explicit spawn
Codex does not auto-spawn. Tell the user once, then run:
- «Spawn 12 expert agents in parallel» — agents in
.codex/agents/*.toml - After merge: «Spawn 6 math agents in parallel»
Prompt template for each expert
IDEA_BRIEF:
<paste confirmed paragraph>
TASK: Execute your role per agent definition. Use web search if available.
Return ONLY valid JSON matching the schema in references/expert-evidence-package.md
for your agent_id. Include sources with URLs when found.
Collect all 12 JSON outputs. Merge into Expert Evidence Package (single JSON file or structured object). Write to biz-eval-evidence.json in workspace temp if needed.
Gate: Do not start Phase 3 until all 12 expert JSONs are received. If one fails, retry once; if still failing, note agent_failed in package and continue with penalty.
Phase 3 — Math layer (6 subagents)
Launch all 6 in parallel after Expert Evidence Package is complete. Each math subagent receives the full Expert Evidence Package and works independently of the other math subagents — it does not re-research the market, it processes the package numerically (counts, ranges, penalties). Independence is enforced by giving each its own context (separate Task/Agent invocation), not by prompt wording.
| Agent | Input | Role |
|---|---|---|
biz-eval-13-evidence-stats | Full package | Evidence & source quality indices |
biz-eval-14-math-model | Package + agent 13 | Formula design & variable weights |
biz-eval-15-scenario-probability | Full package | 4-scenario probability map |
biz-eval-16-unit-economics | Full package | CAC/LTV/churn model |
biz-eval-17-sensitivity | Full package | Top sensitivity parameters |
biz-eval-18-experiments | Full package + math outputs | Validation experiments |
Prompt template for math agents
EXPERT_EVIDENCE_PACKAGE:
<paste full JSON from Phase 2>
TASK: Execute your role. Return ONLY valid JSON per your agent schema.
Do not re-research market — process the package mathematically.
Phase 4 — Deterministic BRS calculation
- Merge expert scores + math agent outputs into
biz-eval-input.json(see references/scoring-formula.md; structure defined in references/evidence-package.schema.json). - Validate, then score:
python3 .agents/skills/business-idea-evaluator/scripts/validate_evidence_package.py biz-eval-input.json
python3 .agents/skills/business-idea-evaluator/scripts/calculate_brs.py biz-eval-input.json
- Use script output as authoritative Business Reality Score. Main agent explains results; does not override numbers.
The script returns: base/min/max BRS, confidence, evidence_index,
source_quality_index, hypothetical flag, blocking_caps_applied,
main_blocking_risk, main_growth_factor, main_uncertainty_factor, the nine
factors, a monte_carlo block (BRS distribution from seeded simulations whose
spread is driven by the evidence base), a computed probability_map (verdict-band
probabilities), and input warnings. Tune runs with --simulations N --seed N.
A worked input/output pair lives in references/example-input.json and
references/example-output.json (also examples/sample-input.json).
If script fails, fix JSON and retry. Do not invent score manually.
Phase 5 — Final report
Render using references/report-template.md.
Verdict must map to BRS:
- ≥65 — test in narrow segment (not "launch fully")
- 45–64 — change model or segment before spending
- 25–44 — weak; only cheap experiments justified
- <25 — do not launch in current form
Always separate: proven by sources | statistical | hypothesis | needs verification.
Subagent installation
Agents live in skill bundle at agents/. Full bootstrap (install + verify + tests):
bash .agents/skills/business-idea-evaluator/scripts/bootstrap.sh
Install only:
bash .agents/skills/business-idea-evaluator/scripts/install-agents.sh
bash .agents/skills/business-idea-evaluator/scripts/verify_subagents.sh
Targets: .cursor/agents/, .claude/agents/, .agents/agents/ get Markdown;
.codex/agents/ gets native TOML via build_codex_agents.py.
Symlinks: .cursor/skills/business-idea-evaluator and .claude/skills/business-idea-evaluator
→ .agents/skills/business-idea-evaluator. User-level ~/.cursor/agents/,
~/.claude/agents/, ~/.codex/agents/ also receive copies.
Resume / partial runs
If user returns after discovery: skip Phase 1 if IDEA_BRIEF confirmed earlier in thread.
If experts done but math pending: start Phase 3 only.
References
- expert-evidence-package.md — per-agent JSON schemas
- evidence-package.schema.json — machine-checkable JSON Schema for the merged input
- scoring-formula.md — BRS formula & blocking rules
- report-template.md — final output format
- evidence-status.md — source grading
- forbidden-phrases.md — banned language
- example-input.json / example-output.json — worked example