Fund Momentum

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

Annotations already cover the safety profile (read-only, idempotent, non-destructive), yet the description adds substantial context beyond them: exact output boundaries (no names, slugs, websites or commitments), the free/no-API-key billing status, the keyless daily allowance, and the small-count reporting convention ('<5', 'none'). This is exactly the behavioral detail an agent needs.

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

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

Dense but front-loaded: the routing instruction comes first, then output scope, then cost, then the pre-search guidance. Every sentence carries distinct, non-redundant information.

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

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

With no output schema, the description fully compensates by stating the return semantics (counts, '<5', 'none') and negative output boundaries. Nothing needed to call or interpret this tool is missing.

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

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

Schema description coverage is 100% and both parameters are thoroughly documented in the schema, including enum normalization and the undisclosed-HQ handling. The description itself adds no additional parameter semantics, so the baseline 3 applies.

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

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

States a specific verb and resource ('does Fund Momentum cover my geography and LP type') and precisely bounds the output ('COUNTS ONLY'). It is unambiguously distinguishable from search_lps, which it names directly.

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

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

Explicitly positions itself as 'START HERE for any question about limited partners' and instructs 'Call this before search_lps to find out whether LP Radar covers what you need' – a clear when-to-use with the alternative named and the selecting condition given.

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

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

Annotations already cover read-only/idempotent safety, but the description adds substantial behavioral context: cost and key tiers, the 7/30-day retention floors, the since_floor_applied disclosure guarantee against silent truncation, and the etag short-circuit returning unchanged:true.

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

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

Front-loads purpose and the not-for-discovery constraint, then packs cost/tier and polling mechanics. Dense but every clause carries distinct information; minor compression could improve scanability.

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

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

With no output schema, the description still explains return behavior (rows, unchanged:true, since_floor_applied) and the full polling contract, so nothing an agent needs to call it correctly is missing.

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

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

Schema coverage is 100%, so params are documented; the description still adds cross-parameter workflow semantics (etag pairs with a prior response, since_floor_applied explains a shortened window) that the flat schema entries do not convey.

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

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

States a specific verb+resource+scope ('return only the funds whose data changed since a given timestamp') and immediately frames it against discovery, distinguishing it from search_funds by name.

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

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

Explicit when-to-use ('FOR STAYING CURRENT, not for discovery'), names the alternative it replaces ('Use this instead of re-running search_funds on a schedule'), and gives the polling workflow condition (send next_since AND etag).

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

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds value by disclosing the response provenance block, the cost/auth model ('free, no API key required'), and the 'THEN' sequencing. No contradiction with annotations.

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

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

Three short sentences with clear labels (THEN, COST) and a direct, actionable warning. Every sentence earns its place; there is no filler or redundant rephrasing of the schema.

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

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

For a single-parameter read-only tool with no output schema, the description covers the input precondition, the response provenance behavior, and the common failure mode. It stops short of enumerating the profile fields, but that is not essential for an agent to invoke this tool correctly.

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

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

Schema description coverage is 100%, and the schema already explains the slug requirement and the warning not to guess it. The description repeats this same guidance but does not add any new parameter-level meaning beyond what the schema provides, so baseline 3 is appropriate.

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

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

The description opens with a specific verb-resource pair: 'get the detailed profile of one fund.' It also specifies the required input source ('using a slug returned by search_funds'), which distinguishes this detail-lookup from the sibling search and signal tools, even without naming them.

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

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

It gives clear, actionable usage guidance: call search_funds first, never guess the slug from the display name, and explains the consequence ('the call is wasted'). It does not explicitly contrast with get_fund_signals or get_gp_profile, so it falls short of the full when/when-not-alternatives bar.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the bar is lower and the description earns credit for adding context beyond them. It discloses the cost model ('included in Pro, or €0.10 per call over MPP if you have no key'), the data-coverage probability (~96% of funds carry signals), and the failure/billing behavior (not_found returned BEFORE payment, so a wrong slug is never charged). This is exactly the kind of behavioral disclosure agents need and is not present in any structured field.

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

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

The purpose is front-loaded in the first sentence, followed by return contents, usage context, then cost and failure behavior. Every sentence earns its place — the cost and not-found details are unusual but valuable for a paid tool. It runs slightly long with the cost sentence being somewhat detailed, but nothing is filler. Well-organized density without waste.

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

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

For a single-parameter read-only tool with no output schema, the description is remarkably complete: it enumerates the return contents (compensating for the missing output schema), explains the input provenance, gives usage timing, discloses cost, data availability probability, and the no-charge-on-not_found guarantee. Nothing an agent needs to invoke this correctly and safely is missing.

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

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

Schema description coverage is 100% — the schema's slug description already explains the provenance ('exactly as returned in the slug field of search_funds') and instructs the agent to call search_funds first rather than guessing. With high coverage, the baseline is 3, and the description text adds no additional parameter meaning. The schema fully carries the load for this single parameter, so no penalty, but also no credit beyond baseline.

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

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

The description opens with a specific verb+resource ('DRILL DOWN on a fund') and enumerates exactly what the tool returns: GP thesis, bullish/contrarian signals, founder dos and don'ts, deployment status, and source URLs. It also distinguishes itself from siblings by scoping to funds 'you already identified with search_funds or get_fund', which sets it apart from search_funds (discovery) and get_fund (basic info). An agent can tell what this does without opening the schema.

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

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

The description gives clear when-to-use context: use it after identifying a fund via search_funds or get_fund, and specifically 'before writing an outreach message to a specific fund.' It implies the workflow sequencing (search first, then drill down), but stops short of explicitly naming exclusion cases or routing to an alternative sibling (e.g., 'for GP background use get_gp_profile instead'). Clear context without formal exclusions earns a 4.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: the cost structure (included in Pro, or €0.10 per call over MPP), and the not_found behavior before any payment for funds with no published GP data. This is genuinely useful operational information that an agent would not otherwise know.

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

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

The description is compact and front-loaded: the core purpose is in the first sentence, followed by usage context, cost, edge-case behavior, and prerequisite. Every sentence earns its place, and the structure guides the agent from what → when → cost → failure mode → prerequisite. No wasted words.

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

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

For a read-only, idempotent tool with 2 well-documented parameters and no output schema, the description covers the essential operational context: purpose, usage, cost, failure behavior, and prerequisite. The only minor gap is that it doesn't describe the shape of the returned GP profiles, but with no output schema and a clear domain concept, this is a small omission rather than a critical one.

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

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

Schema description coverage is 100%, so the schema already documents both parameters well. The description adds value by emphasizing that fund_slug must come from search_funds and should not be guessed, and by clarifying that gp_name is an optional filter. This reinforces the schema rather than merely repeating it, which is appropriate given the high coverage.

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

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

The description opens with a specific verb ('DRILL DOWN to the people') and clearly identifies the resource: General Partner profiles for a fund. It explicitly contrasts with fund-level information ('rather than what the fund does'), which distinguishes it from sibling tools like get_fund. The title and description align, and the purpose is immediately understandable.

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

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

The description explicitly states when to use this tool: when the question is who to approach and what they personally focus on, rather than what the fund does. It also names the prerequisite: 'Requires a slug from search_funds,' and the schema reinforces this by instructing to call search_funds first. This is clear, actionable guidance with no ambiguity.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description goes further by disclosing latency (3–10 seconds, slower than other tools), the reason for it (reasons over every tracked fund), retry/timeout guidance, and the cost model (Pro included, €0.25/call over MPP). These are operational traits the agent cannot get from structured fields.

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

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

Front-loaded with the entry-point framing and output shape, then when-to-use, then latency, then cost. Every sentence carries distinct, actionable information with no filler.

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

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

With no output schema, the description compensates by naming the return shape (top 10 funds with slug, reason, score) and additionally supplies latency and pricing. Nothing an agent needs to invoke and interpret this tool correctly is missing.

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

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

Schema description coverage is 100%, so stage, country and description are fully documented in the schema, including the enum and the 500-char limit. The description adds only the framing that the input is 'plain language', which is marginal. Baseline 3 is correct when the schema does the heavy lifting.

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

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

States a specific verb and resource ('describe a startup in plain language and receive the top 10 matching funds') and even enumerates the response fields. It explicitly positions itself against the sibling search_funds, so an agent can distinguish the two without opening either schema.

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

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

Names the alternative ('Use this instead of search_funds') and the exact condition that selects it: a qualitative brief rather than a filter, with a concrete example. This is explicit when-to-use and when-not guidance.

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

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

Annotations already mark readOnly/idempotent/non-destructive, and the description adds meaningful context: it is free/no API key, returns a defined field set, and produces a durable profile URL plus slug. This goes beyond the schema but does not cover potential rate limits or ordering, which keeps it from a 5.

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

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

The description front-loads the START HERE directive and filters, then adds cost/auth context and result-field details, with every sentence earning its place. It is slightly longer than minimal, but the slug-routing guidance is high-value.

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

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

With no output schema, the description supplies the key return fields and the critical workflow fact (slug feeds other tools). Combined with high schema coverage and read-only annotations, an agent has everything needed to call this tool correctly.

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

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

Schema covers 100% of parameters with clear descriptions, so description does not need to explain them. It restates stage/country/industry only as high-level filter dimensions and adds no syntax, enum normalization, or limit behavior beyond the schema.

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

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

The description states a specific action ('Search actively deploying venture capital funds') on a clear resource with filter dimensions (stage, country, industry). It also positions itself as the entry point to sibling tools via slug, distinguishing it from retrieval tools like get_fund.

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

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

The description clearly instructs agents to start here for any fund question and to copy the slug for downstream tools, which is strong when-to-use guidance. It does not explicitly name sibling alternatives or state when to skip search (e.g., when a fund slug is already known).

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

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

Annotations already declare this a safe idempotent read, and the description goes well beyond them: subscription/auth requirements, the exact failure mode ('lp_access_required' plus coverage count, never a payment challenge), and null-handling for website. This is unusually complete behavioral disclosure.

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

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

Dense but every sentence carries operational weight (auth, error contract, null semantics, filter advice). The opening 'THEN, for LP Radar subscribers' is an awkward fragment that delays the core purpose, costing a point.

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

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

With no output schema, the description compensates by listing returned fields, and it covers prerequisites, auth, error behavior, and filter semantics. An agent has everything needed to invoke it correctly.

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

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

Schema coverage is 100%, so baseline is 3, but the description adds interpretation the schema lacks — that backs_emerging_managers=true means LPs that have backed a first or second fund, and that this filter is absent from check_lp_coverage. It adds meaning rather than restating the schema.

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

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

States a specific verb and resource ('return limited partner records') and enumerates the returned fields, the filter dimensions, and the 25-record cap. It is clearly distinguishable from siblings like check_lp_coverage and search_funds.

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

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

Explicitly routes the agent: 'Use check_lp_coverage first — it is free', and gives conditional advice ('for a first-time manager that is usually the only filter that matters'). It also names who can call it (LP Radar subscribers) and who cannot (per-call, agent credits, keyless trial).

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