Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add lool-ventures/founder-skills/plugin install founder-skillsWrote 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/skills/lool-ventures/founder-skills/ic-sim)<a href="https://agentmods.dev/skills/lool-ventures/founder-skills/ic-sim"><img src="https://agentmods.dev/badge/skills/lool-ventures/founder-skills/ic-sim.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 | $0.00092 | $0.21847 |
| Opus 5 | $0.00046 | $0.10923 |
| Sonnet 5 | $0.00018 | $0.04369 |
| Haiku 4.5 | $0.00009 | $0.02185 |
Grade C, and why
ic-sim scanned grade C with 1 finding 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
- `to_confirm` = data the materials don't disclose (excluded from `applicable`, like `not_applicable`); >6 of them holds the verdict at `more_diligence` in BOTH directions — capped down from `invest` (thin coverage can't How it starts
The opening of the file, as written. The whole thing — 1,249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IC Simulation Skill
Help startup founders prepare for the conversation that happens behind closed doors — the one where VC partners debate whether to invest. Produce a realistic IC simulation with three distinct partner perspectives, scored across 28 dimensions, with specific coaching on what to prepare. The tone is founder-first: a coaching tool for preparation, not a judgment.
Skill Metadata
- Author: lool-ventures
- Version: managed in
founder-skills/.claude-plugin/plugin.json - Compatibility: Python 3.10+ and
uvfor script execution. - Imports (recommended):
market-sizing:sizing.json— fund alignment and market validationdeck-review:checklist.json— deck quality assessment
- Exports:
report.json→fundraise-readiness,dd-readiness
Skill Execution Model (READ FIRST)
See
founder-skills/references/skill-execution-model.mdfor the full inline-skill execution model (3 dispatch contexts, Mitigation 1+2, producer contract, Cowork quirks, per-symptom triage).
This skill runs inline in the main thread, not as a sub-agent — see the reference above ("Why Inline (Not Forked Sub-Agent)") for the rationale. Sub-agents are deliberately shell-free, so orchestration (producer scripts, artifact persistence) stays in the main thread.
Two dispatch contexts for the sub-agent:
- Context A — Per-step analytical dispatch (Mitigation 1): Steps 5, 6, 6b, and 8 dispatch the ic-sim agent via the
Tasktool. The novel element here is parallel dispatch: Step 6 (PARTNER_ANALYSIS) and Step 6b (PARTNER_REBUTTAL) each dispatch the agent three times simultaneously — one per partner archetype — in a single assistant turn. Step 5 (DETECT_CONFLICTS) and Step 8 (SCORE_DIMENSIONS) are sequential dispatches. The sub-agent does deep analysis, WRITES its output JSON to theOUTPUT_PATHgiven in its prompt (thehandoff/dir), and returns a small receipt. The main thread gates the file withcheck_handoff.py, then pipes it through the producer script. The sub-agent never writes canonical artifacts — only its hand-off file. Step 6b is the real second debate round: each archetype sees the other two's round-1 assessments and either holds its position or moves on stated evidence; Step 7'scompose_discussion.pythen derivesdiscussion.jsonfrom Steps 6 and 6b's six artifacts — never authored by the main thread. - Context B — Post-compose coaching dispatch: The final step dispatches the sub-agent after
compose_report.pywritesreport.md. The sub-agent Reads the stagedcoaching_payload.jsonfrom the hand-off dir (Mitigation 2) — it does NOT read the fullreport.md— composes the coaching commentary, WRITES it to theOUTPUT_PATHhand-off file, and returns a small receipt. The main thread gates the file (check_handoff.py) and inserts it via the sharedinsert_coaching.pyscript (idempotency matrix, uuid-marker replacement, run_id-parity verification — all deterministic). See the reference above for the full Context B contract.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/artifact-schemas.md 22 KB
- references/evaluation-criteria.md 16 KB
- references/ic-dynamics.md 6.8 KB
- references/partner-archetypes.md 9.7 KB
- scripts/_dispatch_json.py 1.9 KB runs code
- scripts/_theme.py 3.0 KB runs code
- scripts/compose_discussion.py 19 KB runs code
- scripts/compose_report.py 78 KB runs code
- scripts/detect_conflicts.py 8.6 KB runs code
- scripts/fund_profile.py 8.4 KB runs code
- scripts/score_dimensions.py 19 KB runs code
- scripts/visualize.py 44 KB runs code
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 Changed · +2 lines 8f300e64a761
- 6d ago First seen · 1,247 lines · 92 tokens per session scan C 77b06055436e
ic-sim is a skill published in the GitHub repository lool-ventures/founder-skills (33 stars, last pushed 5d ago), licensed Apache-2.0. It adds 92 tokens to every session and 21,847 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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