CryptoSocials

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

With annotations already declaring destructiveness, idempotence, and non-read-only status, the description adds concrete behavioral effects: it releases unspent reservations, is free, does not refund or delete completed paid results, and leaves archive data, Lists, and other accounts unchanged.

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 front-loaded with the action and scope, then efficiently states cost and side-effect boundaries. Every sentence adds useful information without repetition.

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?

Given the output schema exists and annotations cover safety traits, the description is nearly complete for the cancellation behavior. It omits how to obtain the operation_id, which would help an agent 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 description coverage is 0%, and the description does not mention the sole required parameter operation_id at all. It therefore adds no semantic meaning beyond the schema's type and pattern.

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 verb and resource: 'Cancel an owned queued or running research request.' This clearly distinguishes it from sibling read/list/recover tools.

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 specifies the applicable state ('owned queued or running') and clarifies that completed paid results are unaffected, giving clear context for when the tool applies. It does not explicitly name alternatives for cancellation or recovery.

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 readOnly, non-destructive, non-open-world behavior, so the bar is lower. The description adds genuinely non-obvious interpretive context: results reflect selected retained evidence rather than a live collection snapshot, which is important for reading the output correctly. It does not cover cost, latency, or why idempotentHint is false.

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?

Two tight sentences with zero filler, and the core purpose is front-loaded before the scope caveat. It is arguably terse for a 13-parameter tool, but no sentence is wasted.

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?

The description conveys the content categories (counts vs coverage diagnostics) and the retained-evidence scope, which partially offsets the missing output schema. However, for a 13-parameter diagnostic tool with no output schema and 31% undocumented parameters, it does not explain the shape of the returned diagnostics or how metrics interacts with the filters.

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 69%, so the schema carries most parameter meaning (asset_ids, chain_ids, author_ids, evidence_class, multichain, full_text_query are all well documented). The description itself adds no parameter-level guidance at all, so it neither compensates for the undocumented fields (metrics, has_media, post_types) nor enriches the documented ones.

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: reading stored counts or coverage diagnostics over an explicit UTC period and scope. The second sentence differentiates it from a whole-dataset or live-watermark tool, though it never names the sibling (measure_evidence/discover_evidence) an agent should compare against.

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?

Usage is implied - diagnostics over a retained/archival period - and the description excludes what it is not ('not all of X or a live collection watermark'). But it never states when to prefer this over measure_evidence, discover_evidence, or read_evidence, leaving the routing decision to inference.

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 declare readOnlyHint=false and idempotentHint=false, and the description usefully adds that successful deliveries are persisted privately to the account and consume shared research credits — cost and side-effect context the annotations do not convey. It also warns that matches are not thematically relevant, an important semantic limitation, though it omits failure modes and whether partial results are billed.

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 sentences, purpose first, with each subsequent sentence adding a distinct fact (matching semantics, delivery persistence and credit cost). Dense but front-loaded and free of filler, though the opening sentence packs several concepts together.

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?

An output schema exists, so return values need not be explained, but the tool is high-complexity (9 params, nested selector grammar, fresh/captured bases) and the description addresses none of that structure. It also omits how this fits the discover → measure → read research pipeline, leaving a large gap for such a complex operation.

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?

With nine parameters, deeply nested selectors, and only 22% schema description coverage, the description must carry parameter meaning, but it explains almost nothing. It gestures at 'explicit stored-data scope' (scope/select) and 'attached/unattached' (discover.entity, include_unattached) yet says nothing about basis.mode fresh vs captured, retain, delivery limits, or how selectors compose.

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 verb and resource: 'Find attached asset or author candidates and separately labelled unattached matches.' It implicitly distinguishes itself from measure_evidence and read_evidence by framing itself as a discovery step, but it never names those siblings or clarifies the division of labour, so the differentiation is only partial.

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?

There is no explicit when-to-use guidance and no mention of the obvious alternatives in the sibling set (measure_evidence, read_evidence, search_authors). The clause 'Matching wording selects evidence; it does not establish thematic relevance' is a scoping caveat rather than routing guidance, leaving an agent to infer when this tool is the right entry point.

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, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuine behavioral context beyond that: membership is 'bounded', results carry truncation state, and the tool is explicitly not a prerequisite for the broader List activity research flow.

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?

Two tight sentences, front-loaded with the core verb+resource and followed by the scoping caveat. Dense but every clause carries information about scope or exclusions; 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 and 6 parameters at 33% description coverage, the definition leaves the agent guessing about pagination mechanics and the request_id/after_id contract. The revision-continuation semantics live only in the schema, and return shape is only gestured at via 'revision and truncation'.

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 only 33% (limit, after_id and request_id are undocumented), so the description carries extra burden. It partially compensates by invoking 'bounded' membership, 'truncation' and 'revision' — which map loosely to limit/revision/section — but adds nothing for after_id or request_id.

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 gives a specific verb and resource ('Read a selected saved List's bounded membership, pins and saved-query references') and explicitly scopes it as metadata inspection. It distinguishes itself functionally from saved-query execution and List editing, though it never names the neighboring list_lists tool that an agent would use to discover a list_id.

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 states clear exclusions — 'not saved-query execution, List editing or a prerequisite for List activity research' — which steers the agent away from plausible misuses. What's missing is the positive routing: no mention that list_lists should be called first to obtain the required list_id.

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 and destructiveHint=false, so safety is covered structurally. The description adds the behavior an agent actually needs to know before calling: the account must be authenticated, and this is a free read that consumes no research credits and returns no source data.

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?

Two sentences, zero filler, with the identifying purpose front-loaded and the billing/scope qualifier second. Every clause carries information an agent can act on.

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 parameterless read with an output schema and full annotation coverage, this is sufficient: what it returns is sketched in the description and formally defined by the output schema, and auth plus cost context is stated. Nothing required 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?

The tool takes zero parameters, so there is no parameter semantics to explain; the baseline for a no-parameter tool is 4. The description appropriately spends its words on output identity rather than inventing parameter behavior.

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 ("Identify") and resource ("the connected CryptoSocials account") and names the fields returned (account ID, display name, email), which clearly separates it from the research-oriented siblings. The phrasing "by its stable account ID, display name and email" is mildly ambiguous — it could be misread as input identifiers even though the schema has no parameters — but the intent is recoverable.

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?

Adds real routing context: "Free authenticated account read; not a research-credit or source-data request" tells the agent this call is cost-free and is not the path to research credits or evidence data. It lacks an explicit named alternative (e.g., get_usage, get_research_balance), so it falls short of full when/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 declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds genuinely new behavioral context — that the call is free and triggers no research computation (no billing/rate impact) — which is not derivable from the 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?

Two short, front-loaded sentences. The returned fields come first, then the cost/side-effect caveat. No filler, nothing redundant.

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?

An output schema exists, so return-value shape need not be explained. Scope ('this account's shared allowance') and cost semantics are both covered, making this complete enough to invoke correctly; only explicit sibling routing 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?

The tool takes zero parameters and additionalProperties is false, so there is nothing for the description to document. Baseline 4 for a no-parameter tool.

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 (Read) and resource (this account's shared research credit balance) and enumerates exactly what is returned: allowance, used, reserved, remaining credits, and the allowance period. An agent can tell this apart from get_usage and get_research_status because of the explicit credit-account framing.

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?

'Free; no research calculation' implies this is the cheap, safe way to check credit state, but it never states when to prefer it over siblings such as get_usage or get_research_status, nor any prerequisites. Usage is implied rather than prescribed.

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 readOnly, idempotent, non-destructive, so the safety profile is covered. The description adds genuinely new behavioral context not in the annotations: the call is free and triggers no calculation or provider request, which is decisive for an agent budgeting research calls.

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?

Two short sentences with no filler; the resource list comes first and the cost/no-side-effect caveat second. Every clause carries 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?

An output schema exists, so return-value documentation is not required, and the description still enumerates the three main content areas. For a zero-parameter read tool this is nearly complete, with only sibling differentiation 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?

The tool takes no parameters, so the baseline of 4 applies. There is nothing for the description to clarify beyond what the empty schema already shows.

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 concrete verb ('Read') and names three specific artifacts it returns: the research contract, supported capabilities, and topic guidance. It is distinguishable from siblings like get_research_balance or get_research_status, though the overlap with get_research_guide ('topic guidance') is not addressed.

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 phrase 'Free; no research calculation or provider request' implies this is a safe zero-cost call to make before spending, but it never states when to use this instead of get_research_guide or get_profile. Usage is implied rather than prescribed.

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 readOnly, openWorld=false, destructive=false, so the safety profile is settled. The description does add real behavioral context beyond them — that the call costs nothing and triggers no provider request — which tells the agent it is a cheap, side-effect-free lookup. It stops short of describing what is returned or how the guide is scoped.

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?

Two short sentences with no padding, and the cost/call-behavior note is placed where it matters. It is tight, though the brevity is partly achieved by omitting needed content rather than by efficient phrasing.

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?

No output schema exists, so the description must carry more of the load, yet it never says what the guide returns or what each topic yields. For a tool whose only parameter is an unexplained 11-value enum, the definition leaves the agent guessing at invocation.

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 0% and the single 'topic' parameter carries 11 opaque enum values (overview, live, coins, authors, prices, chains, lists, history, coverage, data, all) with no explanation anywhere. The description's 'topic-specific' restates the parameter name without disambiguating any enum value, so an agent cannot tell which topic to pick for a given intent.

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 names a read of topic-scoped research guidance, which is a recognizable verb+resource, but 'research possibilities, evidence and current connection guidance' is a loosely worded bundle rather than a precise statement of what the guide contains. It gives no differentiation from adjacent siblings such as describe_archive, get_research_capabilities, or discover_evidence, which an agent must choose between.

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?

There is no explicit when-to-use, no when-not-to-use, and no named alternative. The only usage signal is the parenthetical-ish 'Free; no research calculation or provider request', which implies preference over charged operations but states no selection rule.

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, idempotentHint, destructiveHint=false, and openWorldHint=false. The description adds meaningful context beyond those: it is free, triggers no new calculation or fresh observation, and only 'ready' operations expose certain captured data, which is a state-dependent behavioral trait.

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 front-loaded with the core purpose and then adds scoping details. It is reasonably sized, though the second sentence's list of exposed data ('identity observations, complete comparison indexes, labelled facts, original-reading actions') is dense and somewhat jargon-heavy for a status tool whose return shape is already captured by an output 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?

Given a simple read-only tool with one parameter, an output schema, and rich annotations, the description covers purpose, cost, and state-dependent output. The main gap is the absence of parameter semantics for operation_id, but otherwise it provides enough context for correct invocation.

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 0% for the single required parameter, operation_id, and the description does not explain its origin, format, or how to obtain it. It only implies ownership via 'owned operation's state,' which adds minimal meaning beyond the parameter name and pattern in 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 ('Read') and resource ('owned operation's state and accounting'), making the core purpose clear. However, it uses 'operation' while siblings use 'research_request' (e.g., list_research_requests, cancel_research_request), so it does not explicitly differentiate itself from those alternatives.

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 implies usage by saying it reads an owned operation's state and is 'Free; no new calculation or fresh observation,' which suggests it is a cheap status-check tool. But it names no alternatives, no when-not conditions, and no prerequisites for obtaining the operation_id.

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 and destructiveHint=false, so safety is covered. The description adds real value beyond them: the call is free (no credit consumption), transport limits are a separate concern, and 'a period end alone does not guarantee renewed credits' corrects a likely agent misconception about credit renewal.

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 tight sentences, front-loaded with the resource and its contents before the caveats. Every clause carries information, though the renewal caveat is slightly cryptic in phrasing.

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?

No output schema exists, and the description compensates by enumerating the returned fields, while annotations cover the safety profile and the schema covers pagination. Only the absence of explicit alternative-tool routing keeps it short of complete.

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 limit and cursor are fully documented in the schema, and the description's mention of 'paged usage receipts' only echoes that. No additional syntax or format detail is supplied, 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 ('Read') and resource, and enumerates exactly what is returned: allowance, used, reserved and remaining credits, operation costs, and paged usage receipts. This clearly separates it from research-oriented siblings like get_research_balance or get_research_capabilities, though it never names an alternative explicitly.

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?

'Free' and the note that 'transport limits are separate' hint at context, but the description never states when an agent should call this versus get_research_balance or get_research_capabilities. Usage is implied rather than routed.

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, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds the notable behavioral fact that returned identity+revision is usable without expanding membership, and gestures at pagination ('exact continuation where needed'), but does not state cursor semantics, page limits, or what happens when the account has no lists.

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?

Two tight sentences with no filler, and the return payload (IDs, revisions, continuation) is front-loaded. Slightly dense jargon ('exact continuation') is the only cost.

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?

There is no output schema, so the description does usefully enumerate the return fields and the practical use of identity+revision. However, for a 3-parameter paginated tool with two undocumented parameters, an agent still lacks enough to page correctly or understand request_id, so it is only minimally viable.

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 only 33%: limit is documented in the schema, but after_id and request_id carry no description anywhere. The phrase 'exact continuation where needed' vaguely gestures at the cursor but does not explain that it is supplied via after_id, nor what request_id is for (idempotency/deduplication). With low coverage the description should compensate and does not.

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 ('List this account's accessible saved Lists') and specifies what is returned (IDs, revisions, continuation). It implicitly separates itself from the sibling get_list by being the plural, account-scoped enumeration, though it never names the alternative explicitly.

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 hints at a downstream use case ('Activity research can use a returned List identity and revision without expanding its displayed membership'), which implies when the tool is useful, but it never states when to prefer this over get_list or search-style siblings, and gives no exclusions or prerequisites.

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 (readOnlyHint=true, destructiveHint=false, openWorldHint=false), yet the description still adds real value: it discloses that no source is auto-selected and no missing history is fetched, so the agent understands this is pure metadata discovery, not a fetch/backfill. That is exactly the kind of context annotations do not provide.

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?

Two tight sentences, front-loaded with the core action and immediately followed by the scoping caveats. No filler or redundancy.

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 enumeration tool with no output schema, the description conveys the return categories (identities and candle intervals) and the key constraint that sources/coverage stay separate with no backfill. It could say more about pagination, but the cursor/limit parameters already carry that.

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 43%, so the schema only partially documents the 7 parameters (limit, cursor, time_axis have text; asset_id, date_from, date_to, request_id do not). The description reinforces 'exact asset and UTC period,' nudging toward the required triplet, but adds no syntax or format detail and is silent on cursor, limit, time_axis, and request_id.

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?

Specific verb (List) plus resource (stored price-series identities and available candle intervals) scoped to an exact asset and UTC period. An agent knows exactly what is enumerated, though no sibling is named to sharpen the contrast (none is a close analogue anyway).

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?

No explicit when-to-use or when-not-to-use guidance, and no alternatives are named among siblings like read_price_context or discover_evidence. The sentence 'Sources and coverage remain separate; no source is selected automatically' describes behavior rather than when to pick this tool over another.

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 safety (readOnly, idempotent, non-destructive, closed-world), so the description earns credit for adding new context: a bounded recency window, zero cost, account/connection visibility scoping, and an explicit statement of what is excluded (no source text, no new calculation). It does not explain the bound's size or pagination behavior.

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?

A single front-loaded sentence with the verb and resource first, followed by a compact cost/boundary clause. Dense but nearly waste-free; the trailing fragment after the semicolon is slightly clipped but still informative.

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 parameters, an output schema present, and rich annotations, the description only needs to convey scope, cost, and boundaries – all of which it does. The 'bounded' window size is left undefined, which is the one minor gap.

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?

The tool takes no parameters, so the baseline is 4; there is nothing for the description to clarify beyond the schema. It correctly adds no redundant parameter prose.

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?

Names a specific verb (Read) and resource (bounded recent research-operation metadata) and enumerates the payload fields: request IDs, states, recorded credits. This clearly separates it from siblings like get_research_status, get_research_balance, and recover_research_result. It stops short of explicitly naming which sibling it displaces.

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?

Usage is implied rather than stated: 'no source text or new calculation' hints that read_evidence or measure_evidence serve those needs, and 'Free' signals it is cheap to call. There is no explicit when-to-use or when-not-to-use routing against the many adjacent research siblings.

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 is not read-only, not idempotent, not destructive, and closed-world, so the safety profile is partly covered. The description usefully adds that missing observations remain unknown and that successful deliveries are saved privately and consume shared research credits, but it omits other operational traits such as delivery persistence details or retry behavior.

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 front-loaded with the core purpose and uses dense sentences with little obvious padding. Some phrases are telegraphic and under-explained, but each sentence generally contributes a useful behavioral or parameter detail.

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?

This is a complex tool with nine parameters, nested objects, low schema description coverage, and several modes such as fresh versus captured basis. The description does not provide enough operational context for an agent to confidently construct a request without consulting additional documentation.

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 only 22%, so the description carries a heavy burden for explaining parameters. It clarifies a few grouping and top behavior details, but leaves major inputs like basis modes, retain, delivery, metrics selection, comparisons, order, windows, and most selector kinds unexplained.

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 the tool produces full-scope counts, engagement metrics, and comparisons, which is a clear high-level purpose. It does not explicitly name competing siblings like discover_evidence or read_evidence, so an agent still has to infer the boundary between measuring versus reading or discovering evidence.

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?

There is conditional guidance for specific group_by values, such as asset_selected requiring a positive selector and asset_all_attached grouping every attached asset. However, it never states when to use measure_evidence instead of siblings like discover_evidence, read_evidence, or resolve_assets, and it provides no clear 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 declare the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false), and the description adds genuinely new context: successful deliveries are saved privately to the account, consume shared research credits, and unavailable receipts fall back to full delivery. Credit consumption and persistence are the kind of side-effect disclosure annotations do not provide.

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 main action is front-loaded, but the prose is dense and abstract – 'Selected posts, context, reused wording and delivery coverage remain distinct' is opaque and does not obviously help an agent decide anything. Several sentences restate schema concepts rather than earning their place.

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?

An output schema exists, so return values need not be explained, and the description covers side effects and reuse/fallback behavior. For a 9-parameter, deeply nested tool it still leaves usage routing and the many selector kinds entirely to the schema, and it never clarifies the fresh-vs-captured operating model.

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?

With schema coverage at 33% but richly described nested objects (selector, reading, basis all carry inline explanations), the schema already does much of the work. The description maps 'fresh or retained' onto the basis modes and gestures at delivery/reuse semantics, but adds little concrete parameter meaning beyond what the schema documents.

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 names a specific verb (Read) and concrete resources (stored post versions, recorded counters, source citations, reply/quote/repost context). It is clear about what the tool returns, but it never distinguishes itself from siblings like discover_evidence or measure_evidence, so the agent must infer the boundary.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. The phrase 'explicit fresh or retained selection' hints at two bases but does not tell the agent when each applies or how this tool relates to discover_evidence/measure_evidence.

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 are only bare booleans (readOnlyHint=false, no destructive statement), so the description carries meaningful extra burden and pays part of it: it discloses that successful deliveries are saved privately to the account and consume shared research credits, and that provenance/gaps are preserved. It omits retry/idempotency behavior and permission requirements, keeping it short of 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?

Four short sentences, front-loaded with the verb+resource before constraints and cost. Some phrasing is abstract ('genuine gaps', 'remain distinguishable'), but nothing is redundant.

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?

An output schema exists, so return values need not be explained, and the description covers purpose, cost and side effects. For a 9-parameter, deeply nested tool with low schema coverage, however, it leaves operational details (how selectors, windows and price modes interact) to the schema and a referenced guide.

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 low (33%), so the description should compensate more than it does. It gestures at key concepts ('explicit periods', 'observation times', 'Provider candles and derived samples remain distinguishable') that map to windows, time_axis and candle_basis, but it does not explain selector kinds, basis modes, or delivery params; the heavy lifting is done by the nested schema descriptions rather than the prose.

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 names a specific verb and resource ('Read a selected stored price series or candle format over explicit periods') and clarifies the scope ('stored', 'No upstream fetch'), which separates it from fetch/discovery tools. It does not, however, name any sibling tool such as read_evidence or discover_evidence to route the agent.

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?

Usage is implied ('stored' series, 'No upstream fetch or market-event interpretation') but no explicit when-to-use/when-not or named alternative is given. The agent must infer that this is the read path for an already-selected price series from context alone.

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, closed-world). The description adds genuinely new behavioral facts: retrieval is free, it re-runs current access checks at call time, and it replays the exact previously paid response rather than generating new content. It does not describe failure behavior when the operation is not owned/ready.

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?

Two tight sentences, front-loaded with the primary action and followed by the scoping/billing caveat. The second sentence is slightly list-y ('not a new page, fresh observation or additional charge') but each clause disambiguates against a real alternative behavior.

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?

Output schema exists, so return-value shape need not be explained, and for a one-parameter tool the description covers the key gating conditions and the billing implication. Remaining gap is error/edge handling when the operation is not owned, not ready, or no longer accessible.

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 0% for the single operation_id parameter, so the description must compensate. It indirectly constrains the id (it must reference an operation you own that is in a 'ready' state), but says nothing about the UUID format or how to obtain the id.

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 ('Return') and a precisely qualified resource ('an owned ready operation's exact previously paid response'), which is enough to distinguish it from get_research_status (status vs. payload) and from any fresh-observation tool. It does not name a sibling explicitly, so it stops short of a 5.

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?

Gives the selecting context clearly — only for an operation you own that is 'ready' and already paid — and excludes misuse by stating it is 'not a new page, fresh observation or additional charge'. No alternative sibling is named for the case where the operation isn't ready or wasn't paid, so it lacks the explicit routing a 5 requires.

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, non-destructive and non-idempotent semantics, so the bar is lower; the description adds genuinely new information by disclosing the response shape (identity candidates plus explicit 'unknown' or 'merged' states) and the ambiguity pitfall around shared tickers. It does not explain ordering, ranking of candidates, or what a merged state means operationally, which keeps it below 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?

Two tight sentences leading with the verb and the lookup modes, then the return/ambiguity caveat. Dense and front-loaded, though the phrase 'explicit unknown or merged states' is terser than it needs to be and would benefit from one clarifying clause.

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?

There is no output schema, so the description correctly picks up some of that burden by naming the return categories (candidates, unknown, merged) and the ticker-ambiguity behavior, while pagination and argument discipline live in the schema. It stops short of explaining how candidates are ordered or what to do when multiple candidates come back, which is the main remaining gap for a resolution tool.

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 75% and the schema itself documents limit, query and cursor in detail; the description's value-add is enumerating the query input modes including 'exact namespaced contract', which clarifies the precision expected. The only undocumented parameter is request_id, and the description gives no hint about retrieval semantics, so it is not fully compensating.

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 ('Find') and resource ('stored asset identities') plus the four accepted query forms (name, ticker, canonical key, exact namespaced contract), which is far more informative than the tautological title 'Resolve assets'. Siblings are all research/evidence/list tools, so no direct competitor needs to be ruled out by name, but the description also doesn't explicitly say how it relates to read_price_context or discover_evidence.

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 accepted input forms and the caveat that 'a shared ticker does not prove one intended identity' imply when the tool is appropriate, but there is no explicit when-to-use/when-not-to-use statement and no named alternative. An agent can infer the context from the query forms but must guess the boundary with market/price tooling.

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?

The description explains why readOnlyHint is false: an exact missing handle may be recorded locally for coverage review. That is genuine context beyond the annotations, and 'no provider fetch or promise of addition' sets accurate expectations about side effects and guarantees.

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 sentences, front-loaded with the lookup keys and behaviour. The final clause ('no provider fetch or promise of addition') is telegraphic but earns its place by bounding expectations.

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?

There is no output schema and the description never indicates what a result looks like (candidate fields, match certainty, next_cursor). Pagination is covered only by the schema, leaving the return contract underspecified.

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 75%, so limit, cursor and request_id are already documented in the schema. The description restates the query forms but adds nothing new about pagination, limits or the request_id correlation parameter.

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 (Find) and resource (stored author candidates) plus the three lookup keys: platform user ID, handle prefix, display name. 'Stored' implicitly separates it from live-fetch siblings like get_profile, but no sibling is named.

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?

Usage is implied by the lookup modes, and the tool explains the exact-missing-handle case, but it never states when to prefer this over get_profile or resolve_assets, nor when not to use it.

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