California Bitcoin

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

Annotations only indicate readOnlyHint=true, while the description adds behavioral traits: the response is deterministic, concise, grounded in a specific knowledge source, and free. This provides useful context beyond the annotations, though it does not detail failure modes or answer formatting. No contradiction exists.

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 a single terse sentence with no real filler. The leading 'FREE.' is arguably unnecessary, but it is short and harmless. Overall structure is acceptable for such a simple tool.

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 one-parameter, read-only Q&A tool, the description adequately states what the tool does, what input it needs, and what kind of output to expect. However, with no output schema and no discussion of out-of-scope questions or when to use a sibling tool, a few gaps remain.

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 schema has zero description coverage for the single 'query' parameter, so the description carries the semantic burden. It implies that query is the Bitcoin question being answered, which gives basic meaning, but it leaves the expected query format and ambiguous cases unaddressed. This earns a baseline 3.

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 clearly states the tool's action: returning a concise deterministic answer grounded only in California Bitcoin maintained knowledge. It identifies both the verb and resource, making the purpose fairly obvious, but it does not explicitly distinguish it from sibling tools like search_bitcoin_knowledge or verify_bitcoin_claim, 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?

The description offers no guidance on when to choose this tool over its siblings, nor does it mention exclusions or alternatives. It simply describes the action without giving context about when a user request should be routed here versus search_bitcoin_knowledge, verify_bitcoin_claim, or deep_ground_bitcoin.

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 annotations already provide readOnlyHint=true, and the description adds important non-obvious context: the $2.50 USD Stripe MPP payment requirement and deterministic behavior. This goes beyond the structured annotations and helps the agent understand cost and reproducibility, though it doesn't detail output or error 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 a single front-loaded sentence with no wasted words. It communicates the cost, the batch limit, the accepted content types, and the deterministic nature efficiently.

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 paid batch tool with no output schema, the description is adequate for invoking it—the agent knows what items to send and how many—but it does not disclose the return format, what a successful response looks like, or how the results relate to the sibling research tools. This leaves a meaningful gap for a tool with no output schema.

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 description names the semantic categories of the items array ('claims, questions, or evidence requests') and the batch size cap, which partially maps to the schema's enum values and maxItems. However, with schema description coverage at 0%, it does not compensate by explaining the accepted string/object structure or the 'text' field, leaving the schema to carry most structural meaning.

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 ('process') and resource ('claims, questions, or evidence requests') with a clear batch scope ('up to 20'). It is understandable and distinct from the siblings in spirit, but it does not explicitly name or contrast any sibling tool like answer_bitcoin_question or verify_bitcoin_claim.

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 a batch use case ('Process up to 20... in one package') but gives no explicit guidance on when to use this tool versus the single-item sibling tools. There are no 'use this when' or 'use that when' instructions, and no exclusions or alternatives are mentioned.

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 provide readOnlyHint=true, so the safety profile is covered. The description adds valuable behavioral context beyond the annotations by disclosing a cost ('PAID $0.50 USD via Stripe MPP') and indicating that the timeline is built from curated, maintained Bitcoin history. This helps the agent anticipate side effects and prerequisites.

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 extremely concise with no filler. The payment disclosure is front-loaded, and the purpose sentence directly follows with meaningful details ('query-specific', 'historical research', 'maintained Bitcoin history'). Every sentence earns its 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?

The core purpose is clear and the readOnlyHint plus payment disclosure cover important context. However, there is no output schema and the description does not describe what the returned timeline looks like, how date filtering or limits behave, or any potential usage constraints. This leaves noticeable gaps for a tool with four parameters and no output schema.

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%, so the description must compensate, but it only implicitly references the 'query' parameter. It provides no additional meaning for 'limit', 'fromYear', or 'toYear', leaving their constraints, defaults, and interaction largely unexplained. The parameter names are somewhat self-explanatory, but the description itself adds little value.

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 clearly states a specific verb ('Build'), a specific deliverable ('a query-specific historical research timeline'), and a data source ('maintained Bitcoin history'). This distinguishes it from sibling tools like search_bitcoin_knowledge or answer_bitcoin_question, which focus on retrieval or answering rather than timeline construction.

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 for creating a timeline from a research query, but it does not explicitly state when to prefer this tool over alternatives, nor does it mention any exclusions. There is enough context for an agent to infer the intended use, but no direct comparison with sibling tools.

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 adds meaningful context beyond the readOnlyHint annotation by disclosing the paid cost ('PAID $1.00 USD via Stripe MPP') and characterizing the output as 'deeper deterministic grounding.' This helps an agent understand the tool's cost and reproducibility, though it does not detail output format or rate limits.

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 concise with two short sentences and no filler. The payment disclosure is relevant for agent decision-making, though front-loading the functional purpose before the payment detail might improve scannability.

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, the description is somewhat sufficient: it states cost, general scope, and output type. However, it lacks details about what the grounding package will contain, how results are returned, and when a caller should prefer this over a sibling tool, leaving moderate ambiguity.

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 explain the 'query' parameter beyond the parameter name itself. The domain and tool title suggest the query is a Bitcoin research topic, but the description provides no explicit semantics, format, or examples to compensate for the missing schema documentation.

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 ('Produce a deeper deterministic grounding package') and identifies the resource scope ('canonical topics, claims, sources, and history'). It conveys more than the title's research label, though it does not explicitly differentiate itself from sibling tools such as get_bitcoin_evidence_pack or batch_bitcoin_research.

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 guidance is provided on when to use this tool versus alternatives. The word 'deeper' implies a need for more thorough research, but there is no explicit when-to-use, when-not-to-use, or alternative routing among the seven sibling tools.

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, so the baseline bar is lower. The description adds meaningful context by disclosing a payment requirement ("PAID $0.50 USD via Stripe MPP") and by listing the evidence package components. There is no contradiction with the read-only annotation because "Build" here implies assembling a response, not modifying external state.

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 short and mostly to the point, but the payment notice is placed before the actual purpose, which hurts front-loading. The core sentence is efficient, but the overall structure prioritizes a billing detail over the tool's function.

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 only one parameter and a read-only annotation, the description does not need to be long. However, it leaves the query semantics unexplained and offers no routing context among seven related sibling tools. The output components it lists are helpful, but the package's exact scope and response format remain 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 description coverage is 0%, so the description needed to clarify what the "query" parameter should contain. It does not; the parameter meaning is only weakly implied by the tool name and package-building phrase. This is a clear gap.

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 uses a clear action, "Build a structured evidence package," and specifies the output contents: claims, source classes, provenance, history, and related concepts. This distinguishes the tool's purpose from siblings at a general level, though it does not explicitly name a differentiating sibling.

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 provides no guidance on when to use this tool instead of alternatives like answer_bitcoin_question, verify_bitcoin_claim, or get_bitcoin_topic. It also does not state what kind of query is appropriate or any exclusions.

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?

readOnlyHint=true already establishes that this is a safe read operation. The description adds that the result includes source and provenance metadata and that the operation is FREE, which are useful behavioral details beyond the annotation. It does not mention error handling or availability, but for a simple read-only get-by-id tool this is acceptable.

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 one short sentence with the action, resource, and key scope all front-loaded. 'FREE.' is an extra but brief cost signal, and every clause adds meaning. There is no unnecessary repetition of the tool name or title.

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 lookup with a readOnlyHint annotation, the description is mostly complete: it states what is retrieved and what metadata is included. There is no output schema, so the description partly covers return expectations, but it does not mention what happens when no topic is found or whether the topic body itself is fully included.

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 only parameter is id, and the schema already enforces its pattern and maxLength. The description adds context by saying the id identifies a canonical Bitcoin Knowledge Atlas topic, which is helpful but does not add format details beyond the schema. For a single simple parameter with 0% schema description coverage, this is adequate.

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 (Retrieve), a specific resource (canonical Bitcoin Knowledge Atlas topic), and the lookup key (by id), plus the additional output context (source and provenance metadata). This clearly distinguishes the tool from siblings like search_bitcoin_knowledge or get_bitcoin_evidence_pack, which are not canonical single-topic lookups by 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?

The description implies the tool should be used when you already have a topic id and want the canonical single topic, but it does not explicitly contrast this with search_bitcoin_knowledge or other alternatives. There is no when-not-to-use guidance or mention of sibling tools, so the agent must infer the right context.

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 readOnlyHint annotation already establishes that the tool is safe. The description adds some scope context ('canonical Knowledge Atlas and related history') and a free-to-use signal, but does not mention pagination, ranking, or result behavior. It does not contradict the annotation.

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 core sentence is concise and front-loaded, but the leading 'FREE.' is unrelated filler that does not help an agent invoke the tool. The structure is acceptable but could use a richer explanation.

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 search with two simple parameters, the description is minimal but leaves gaps: it does not explain what the Knowledge Atlas contains, how results are returned, or when to use this tool relative to the seven siblings. The annotations cover safety, but the description lacks enough context for confident selection.

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 schema documents query and limit with types, defaults, and bounds, but the description provides no additional meaning about how to form the query or how limit affects results. With 0% schema description coverage, the description should compensate; it 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?

The description identifies the tool as a search operation over a specific resource ('California Bitcoin’s canonical Knowledge Atlas and related history'), which is more specific than the title. It clearly conveys the verb and resource, distinguishing it from answer/verify tools, though it does not explicitly differentiate from sibling search-like 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?

There is no guidance on when to prefer this search tool over siblings such as get_bitcoin_topic or batch_bitcoin_research. The description only states what the tool does, not the conditions that would select it.

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 only indicate readOnlyHint=true, so the description adds value by disclosing a payment/cost element ('PAID $0.50 USD via Stripe MPP') and the verification behavior against canonical statements. It does not contradict the annotations and provides useful behavioral context beyond them.

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 brief and mostly front-loaded, stating the cost first and then the core action. The payment sentence is unusual but earns its place as behavioral context, and the rest is tight 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?

For a single-parameter tool with no output schema, the description adequately covers input, action, and the shape of results ('supported, unsupported, or uncertain evidence'). It does not explain what 'canonical maintained statements' consist of, but that is not essential for calling the 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 0%, and the only parameter is 'claim'. The description compensates by explicitly using and defining the claim as the object of verification, giving the parameter practical meaning beyond the bare schema name.

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 ('Verify'), a clear resource ('a claim against canonical maintained statements'), and the three possible outcomes ('supported, unsupported, or uncertain evidence'). This distinguishes it from sibling tools like answer_bitcoin_question or search_bitcoin_knowledge, which target different actions.

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 makes clear that this tool is for verification of claims rather than open-ended answering or research. It does not explicitly name alternatives or exclusion conditions, but the purpose is specific enough for an agent to infer when to select it.

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