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find_vcs

UNDERSTANDING — Find venture-capital firms by name, thesis tags, or category. Each carries a network-matched, rated portfolio graph. Sort by portfolio_on_network (default), portfolio_total, portfolio_rating, or name. Understanding plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree text over name + description.
pageNo
sortNo
tagsNoTag slugs.
limitNo
contextNoOptional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable.
categoryNoFirm category, e.g. "Venture Capital".

TDQS

B3.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and partially meets it: it discloses that each result 'carries a network-matched, rated portfolio graph' and specifies the default sort. It does not cover output shape, pagination behavior, or what the 'Understanding plan' entails, leaving some behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is tightly packed: purpose, result payload, and sorting are each stated in a single clause with no fluff. The 'Understanding plan' tag is brief and adds plan context without bloating the text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only search tool with 7 parameters and no output schema, the description is adequate for basic invocation: criteria, sort, and result contents are covered. However, absence of alternatives/routing, output format, and plan/tier explanation leaves the complete picture slightly out of reach.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 57%, and the description adds useful mapping between the search criteria ('name, thesis tags, or category') and parameters, plus the default sort option. Page, limit, and context are left for the schema to carry, which is partially acceptable but not fully compensated at this coverage level.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a concrete action and target: 'Find venture-capital firms by name, thesis tags, or category,' which clearly identifies the resource and filtering criteria. It does not explicitly differentiate from overlapping siblings like find_investors or get_vc, so it misses the top mark.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given about when to prefer find_vcs over the many find_* siblings or get_vc, nor are exclusions or prerequisites stated. The 'Understanding plan' label hints at a plan restriction, but its implications are never explained.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0
Disambiguation3/5

Most tools are clearly separated by artifact type or resource (find_mcp vs find_openapi vs get_provider vs get_api), but the sheer volume creates some genuinely confusable clusters: apis_io_search vs find_apis vs find_artifacts, and insights_adoption vs insights_dimensions vs find_company_insights. Several readiness-related tools (what_can_i_fix, simulate_fixes, readiness_gates) also share a conceptual boundary, though their descriptions do help.

Naming Consistency3/5

The dominant patterns (find_*, get_*, cohort_*, compare_*) are consistent and predictable, but the set mixes in irregular names like apis_io_search, tag_group_tags, what_can_i_fix, whats_changed, and resolve. These deviations are readable but break the otherwise regular verb_noun convention.

Tool Count2/5

106 tools is far beyond the typical well-scoped server and will impose a heavy selection burden on agents. The server covers a genuinely broad domain (catalog search, ratings, cohorts, agent readiness, lists, exports, feedback), so the count is defensible in scope, but it is still too many to navigate efficiently.

Completeness5/5

The surface is remarkably complete: search and browse, single-entity detail, comparisons, cohort analytics, agent-readiness assessment, saved searches, list management, feedback/correction flows, and full dataset exports are all covered. There are no obvious dead ends, and even minor operations like re-running saved searches or simulating fixes are present.

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