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{
  "description": "Map capital flow across a space: who is funding an indication, mechanism, target, or investor set, how much, and how it has moved over time. Use for market-level money questions, for example 'who is funding TL1A', 'how much has gone into obesity'. Use trace-financings when someone wants the round-by-round record for one company, and competitive-pipeline for drug programs rather than capital.",
  "included_files": [
    {
      "relative_path": "LICENSE",
      "size_in_bytes": 802
    },
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 326
    },
    {
      "relative_path": "references/evidence-research.md",
      "size_in_bytes": 4449
    }
  ],
  "name": "funding-landscape",
  "skill_md_contents": "---\nname: funding-landscape\ndescription: \"Map capital flow across a space: who is funding an indication, mechanism, target, or investor set, how much, and how it has moved over time. Use for market-level money questions, for example 'who is funding TL1A', 'how much has gone into obesity'. Use trace-financings when someone wants the round-by-round record for one company, and competitive-pipeline for drug programs rather than capital.\"\n---\n\n# Funding Landscape\n\n## Using this skill\n\nUse the connected Maven Bio MCP server at `https://mcp.mavenbio.com/`. Follow the user's explicit scope, depth, and output preferences; the workflow and output structure below are defaults. Report coverage limits instead of silently narrowing an explicitly requested set.\n\nHyphenated primitive names refer to other skills in this Maven Bio bundle. Consult the relevant skill when composing its workflow. Use the available MCP tool schemas for arguments; pass document identifiers to `read_document` through `ids`, and include a claim-specific `query` when using `format=\"citations\"`.\n\nThis workflow produces a capital-flow intelligence package for a space, not a drug-program landscape.\n\n## Use When\n\n- an investment team wants recent funding activity in an indication, mechanism, or target\n- a BD or corp dev team wants the round-size and investor-mix picture for a space they are evaluating\n- a portfolio strategist wants to gauge capital momentum, sentiment, or new-entrant pressure in a competitive area\n- the question is about money flowing into a space, not about which drugs are in development there\n\nFor the drug-program-centric question (which assets are in trials, at what phase, with what mechanism), use `competitive-pipeline` instead.\n\n## Primary Primitives\n\n- `enumerate-entities` to scope the right indication, mechanism, target, or investor set\n- `trace-financings` for round-level capital activity\n- `synthesize-evidence` for any quantitative claim that will be cited (totals, top-investor lists, deal cadence)\n\n## Optional Primitives\n\n- `trace-events` for post-round announcements, deals, or regulatory milestones tied to recipients\n- `profile-entity` for a focused dive on a notable recipient or investor surfaced by the round set\n\n## Output Contract\n\nReturn a funding intelligence package that can include:\n\n- scope summary (which indication / mechanism / target / investor set the package covers, and the time window)\n- total raised in window (USD), with the confirmed and unconfirmed slices reported separately\n- round count and round-type distribution (Pre-Seed through IPO and beyond)\n- top recipients by total raised, each with round count and most recent round\n- top investors by activity in the space (count of rounds participated, lead-investor signal where derivable)\n- deal cadence (rounds per quarter or per month) so the reader can see acceleration or cooling\n- notable rounds (top by value, oversubscribed, strategic investor presence, post-IPO follow-on)\n- market signal interpretation (acceleration vs cooling, sub-mechanism momentum, investor concentration)\n- explicit gaps and boundary conditions\n\n## Aggregation Shortcuts\n\nWhen the question is about distributions, rankings, or trends rather than individual rounds, prefer `aggregate_records(entity_type=\"financing\", ...)` over enumerate-and-count. Canonical calls:\n\n- Round-type distribution: `query=\"rounds in {scope} by financing type with total value and count\"`\n- Deal cadence: `query=\"rounds in {scope} by quarter since {date}\"`\n- Top investors: `query=\"rounds in {scope} grouped by investor, top 25\"`\n\nThe `investors` field is M2M-exploded (one round with three investors counts in all three groups). `total_value_input_count` separates confirmed-value rounds from unconfirmed. Use `get_financings` for the round-level evidence that backs any claim you cite.\n\nGovernment grants (NIH, NCI, NIAID, Innovate UK, Bpifrance) will top investor-count rankings if not filtered. For BD/corp dev personas, exclude grant funders or report them in a separate slice.\n\n## Core Research Pattern\n\n1. **Scope** the right ontology entry. Resolve the indication / mechanism / target (or, for a broad area, a top-level indication) with `match_entity`, or use the recipient-side filters (indication / modality / mechanism / target) surfaced through `search_entities(\"financing\", ...)`. Define the time window explicitly. Decide whether the scope is recipient-side, investor-side, or both.\n2. **Enumerate** the round set. For structured filters use `get_financings` directly; for ontology-anchored or fuzzy queries use `search_entities(\"financing\", ...)`. Page through the full matching set, not a sample. For the aggregate shape (round-type distribution, deal cadence, top investors), use `aggregate_records` to get the picture in a single call before drilling into individual rounds.\n3. **Augment** with documents and events. For high-signal rounds (top by value, strategic investor, recent), pull supporting `document_ids` via `read_document`, and catch newer rounds with `get_financings` scoped to the company (financing recency is not in `get_recent_events`).\n4. **Reconcile** before finalizing. Compare round count and total raised against any prior expectation or anchor knowledge. If counts look suspiciously low, broaden the scope or rerun with a sibling ontology axis (parent indication instead of subtype). If they look noisy, separate the confirmed-value slice from the unconfirmed slice.\n\n## Workflow Rules\n\n- treat the unconfirmed-value slice as a separate visible bucket; never aggregate `total_value_usd: null` rounds into \"total raised\" without a footnote\n- when reporting deal cadence, anchor on quarter-ending dates and call out the trailing-quarter window explicitly\n- when reporting top investors, distinguish lead-investor presence (derivable from round documents) from participating-investor presence (the raw investor list)\n- pair recent funding cadence with `get_recent_events` so the reader sees both the round and any post-round announcements (clinical readouts, deals, FDA actions) that contextualize the capital\n- for VC and corporate venture investor lookups, the natural axis is `aspects=[\"investments\"]` on `research_entity`, not the recipient-side filters\n- do not present a funding landscape as proof of clinical or regulatory progress; the two layers are independent and the reader needs both\n- distinguish private capital (financing rounds) from public-market signals (market cap, cash, runway from financial statements). The latter lives on `get_financials`; mention it when comparing public-comp valuations\n- when the user is a BD or corp dev team sizing acquisition targets, surface a runway-implication slice: companies with thin recent funding, an old last round, or an aging Series B+ are candidate signals (combine with `get_financials` on public comps for full posture)\n- For independent evidence workstreams, follow the [evidence research procedure](references/evidence-research.md) for each scoped pass, then reconcile the claims before synthesis. Run passes sequentially, or in parallel when the host supports it and the task authorizes it.\n\n## Fallback Rules\n\n- if the indication fails to resolve, retry with the raw name and move disambiguating text into the optional context hint; if it still fails, broaden to the parent indication and note the scope drift\n- if `get_financings` returns zero rounds for a structured query, retry the same intent through `search_entities(\"financing\", ...)` and check whether SSF resolves the scope differently before concluding no activity exists\n- if the round set is suspiciously sparse, run sibling-axis enumeration (parent indication, broader mechanism class) and preserve the broader set as discovery scaffolding before finalizing\n- if the round set is large and noisy, partition into core confirmed rounds (with supporting documents read in-session) and watchlist rounds (structured-only or thin documents) rather than collapsing every round into the headline narrative\n- if a notable round's investor list is dominated by stub companies (`display_only=True` thin profiles), preserve the asymmetry; do not promote a stub-only round to the same evidence tier as a fully-resolved round\n- if host web fetch is blocked, augment with `search_documents` plus `read_document` against round-linked documents rather than repeated blocked fetches\n- if a workflow gap remains after the above (e.g., the user wants a filter that does not exist on `get_financings`), record it explicitly in the output rather than silently approximating it with a filter that means something else\n\n## Persona Notes\n\n- **Investment teams** typically want recent activity in a thesis space, lead-investor signal, and round-size distribution. Default the time window to trailing 12-24 months and lead with notable rounds plus deal cadence.\n- **Pharma BD / corp dev** typically want acquisition-target screening or deal-target identification. Combine the recipient-side round set with `get_financials` on public comps and a runway-implication slice. Surface candidates with thin or aging funding as signal.\n- **In-house pharma portfolio / strategy** typically want competitor capital posture and new-entrant detection. Anchor the scope on the same mechanism, target, or indication their internal asset operates in, and pair with `competitive-pipeline` for the program-level view.\n"
}

SHA-256 of public snapshot: dc587048377409cb47503e72eac54f0df6fc0cc34921bcc25daf5d72ef17da7d