Enumerate Entities

This primitive is for scope definition, not final deliverable formatting.

Use When

• the user wants the universe of entities in a space
• you need the candidate set before benchmarking or profiling
• the first problem is recall and scoping, not narrative synthesis

Core Tools

• match_entity
• search_entities
• research_landscape
• fetch_related
• get_financings for financing-criterion enumeration (e.g., recipients of recent Series B+ rounds in a space, or rounds led by a specific investor set)

Output Contract

Return a structured entity list with:

• entity id
• entity name
• entity type
• why it is in scope
• evidence status for the inclusion decision
• gaps or ambiguity notes

This primitive is allowed to return citation_status: unresolved when the output is still discovery scaffolding rather than document-backed evidence.

When Enumeration Is Not Enough

Enumeration answers "which entities are in scope". It does not answer questions that require per-row evaluation against custom criteria rather than catalog metadata:

• the user wants to filter the enumerated set by conditions that require LLM judgment (e.g., "targets KRAS G12C specifically", "has an oral formulation")
• the user wants enrichment dimensions extracted per entity with evidence (e.g., "lead indication", "differentiating feature")
• the evaluation criteria are custom to the question, not fixed catalog fields like phase or mechanism

enumerate-entities defines the candidate universe; synthesize-evidence evaluates it. When the universe is larger than the evaluation budget, narrow the enumeration criteria rather than reducing the evidence gathered per entity.

Baseline, Not Completion

Enumeration defines the baseline universe. It does not, by itself, complete a master analysis.

For broad analyses such as landscapes, pipelines, benchmark sets, or strategic maps:

• use this primitive to establish the candidate set
• then run a document augmentation pass with search_documents, read_document, and relevant event checks
• reconcile newly surfaced entities, recent changes, or contradictory evidence before treating the set as final
• run a scope-reconciliation gate before downstream finalization: compare the candidate count, class coverage, phase/status coverage, and known anchor entities against the requested scope
• if the candidate set is suspiciously sparse, too broad, or missing expected anchors, treat that as a research gap and broaden/narrow the search before finalizing

If the entity list is still only discovery scaffolding, keep that explicit in the output.

Fallback Rules

• If a resolver-backed tool fails on a composite name, retry with the raw entity name and move sponsor/company text into the optional context hint.
• Use match_entity when the task starts from one known entity name and you need the canonical Maven entity.
• When calling match_entity, keep the raw entity name in name and put sponsor/company/disambiguating text in context.
• When calling research_landscape, keep the raw indication name in indication and put extra disambiguating text in context.
• Use search_entities when the task is to discover or enumerate entities by criteria, filters, or market description.
• For financing-criterion enumeration (recipients of rounds, investor-led sets, capital-flow scoping in a space), use get_financings directly when the question is structured (recipient / investor / type / value / date), or search_entities("financing", ...) when the question is a natural-language phrasing. The recipient-side ontology axes (indication, modality, mechanism, target) are reachable through search_entities("financing", ...) even when not exposed as typed get_financings params.
• If the baseline set looks suspiciously sparse, follow with search_entities and a document augmentation pass.
• If the baseline set looks noisy or over-broad, preserve a watchlist/exclusions tier rather than collapsing every candidate into the core set.
• If document search surfaces new candidates not seen in the structured layer, preserve them explicitly for reconciliation.

Aggregation Shortcut

Once a universe is scoped, aggregate_records(entity_type=X, query="...grouped by Y") answers "how many in each bucket" without paginating the full enumeration. Use it as a sanity check on the size and shape of the enumerated set before downstream skills consume it.

Quality Bar

• use explicit scoping criteria
• separate in-scope, borderline, and excluded entities when useful
• do not present enumeration as proof of a downstream factual claim
• do not treat structured enumeration as the final truth for a master analysis without a document augmentation pass
• do not treat an entity set as complete until the scope-reconciliation gate has been run or the remaining uncertainty is stated explicitly
• note ambiguity when the entity set may be incomplete