agentsclimarketplace

Raise match

Skill AndrewTtofi/spine/skills/raise-match

Use to deeply analyse whether a specific VC fund fits your startup — spawns four parallel research sub-agents (thesis, portfolio, people, deal), scores the fit across eight dimensions out of 100, and writes a complete fund dossier with the warm-intro path, perks, and a pursue/warm-up/no-go verdict. Run after raise-vet clears the fund. Use when asked to "analyse this fund", "does this VC fit us", "research a fund", or "should we pitch this investor".From its SKILL.md

Install
npx -y skills add AndrewTtofi/spine --skill raise-match

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SKILL.md

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raise-match — the gated, four-agent fund dossier

The workhorse of the track. Where raise-vet asks "is this fund real?", raise-match asks "does it fit us?" — and answers it with real research: four sub-agents in parallel, an evidence-cited fit score, and a single dossier the rest of the track builds on. It is the sole assembler of dossier.md.

Invocation

raise-match <fund name>

Steps

1 — Load context and the vet gate

Read .spine/raise/profile.md (stop → raise-init if absent). Derive the fund slug. Read .spine/raise/funds/<slug>/dossier.md if it exists and branch on legitimacy_score (see ADR 0017):

  • < 40 → stop: "This fund scored [N]/100 on vet — likely a poser. Run raise-vet <fund> to review, or move to the next fund." Spawn nothing.
  • 40–59 → proceed, and flag a caution banner in the dossier.
  • ≥ 60, or no vet yet → proceed normally (suggest the founder run raise-vet first if there's no dossier, but don't block).

2 — Fan out four research sub-agents

Read the four prompt templates and fill the profile placeholders ({{FUND_NAME}}, {{SECTOR}}, {{STAGE}}, {{GEOGRAPHY}}, {{ONE_LINER}}, {{TRACTION}}, {{RAISE_AMOUNT}}, {{BUSINESS_MODEL}}, {{CEO_NAME}}, {{CEO_CREDENTIALS}}, {{CTO_NAME}}, {{CTO_CREDENTIALS}}, {{REFERRAL_CONTACTS}}, {{COMPETITORS}}):

Fire all four Agent calls in a single message so they run in parallel. Each prompt must be fully self-contained — sub-agents see none of this conversation. Instruct each to return only its named field blocks: no scoring, no recommendations, no file writes. Wait for all four.

3 — Synthesise and score

Reconcile conflicting data (note the conflict and its sources). Score eight fit dimensions, each citing specific evidence from the returns — never an uncalibrated guess:

DimensionMaxEvidence
Sector fit20thesis: focus clusters
Stage fit20thesis: stage + portfolio: entry-stage reality
Thesis alignment20thesis: mandate + quotes
Team–fund fit10people: fit signals
Traction signal fit10portfolio: traction bar
Check size / terms10deal: check size + instrument
Geographic fit5thesis/deal: geography
Network / warm path5people: warm-intro paths

Fit score = the sum (max 100). Recommended action: ≥75 → pursue · 50–74 → warm-up · <50 → no-go. If fewer than three sub-agents returned usable data, downgrade the action one tier and note the gap.

4 — Write the dossier (whole)

Rewrite .spine/raise/funds/<slug>/dossier.md end to end using references/dossier-format.md. Preserve the ## Legitimacy section if raise-vet wrote one, and complete the handoff header (fit_score, recommended_action, updated). Then report the fit score and verdict, and the next step: pursue → raise-pitch / raise-outreach; warm-up → name the lowest-scoring dimension to fix; no-go → state the primary mismatch and suggest raise-funds.

Spine I/O

  • Reads: .spine/raise/profile.md; .spine/raise/funds/<slug>/dossier.md (vet stub).
  • Writes: .spine/raise/funds/<slug>/dossier.md (full dossier; sole assembler).

Notes

  • All scoring lives here, not in the sub-agents — so calibration is in one place and scores stay comparable across funds.
  • Never fabricate portfolio names, check sizes, or partner quotes — cite sources or mark Unknown. Each prose section stays under ~200 words; lead with tables.
  • This is the only skill that writes the full dossier.md (ADR 0016).

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