JYOTINT Sealed Forecasts

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

No annotations are provided, so the description fully discloses behavioral traits: it returns verbatim passages (never generated/paraphrased), cites source pages, and reports lack of matches truthfully. It does not cover authorization or rate limits, but for a read-only tool, this is sufficient.

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 paragraph that packs essential information: purpose, behavior, usage guidance, and fallback behavior. It is front-loaded with the core action and adds necessary details without excessive verbosity. Minor redundancy exists but does not detract significantly.

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 no output schema, the description adequately explains the return format (verbatim passages with source citations) and fallback behavior. It covers the tool's scope and limitations, making it complete for a retrieval Q&A tool without needing an 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 coverage is 100% (both 'query' and 'limit' have descriptions). The description adds minimal extra meaning beyond the schema: it reinforces that 'query' is natural language and 'limit' defaults to 3 with max 6. The baseline of 3 is appropriate given full schema 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 clearly specifies the tool's purpose: answering questions about JYOTINT by retrieving verbatim passages from the operator's published site copy. It distinguishes itself from sibling tools by emphasizing that outputs are never generated or paraphrased, preventing hallucination.

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 explicit guidance on when to use the tool ('Prefer this for any 'what does JYOTINT say about X' / 'why' / 'how does it work' question'), including behavior when no match is found. It does not explicitly mention alternatives or when-not-to-use, but the context is clear.

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?

With no annotations, the description transparently discloses that the tool returns a full record including verbatim claim, grade, outcome, sources, and seal hash. It does not mention error handling or rate limits, but such omissions are minor for a simple fetch operation.

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 efficiently convey the action, parameter, and return content. The first sentence front-loads the purpose, and the second lists return fields without 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?

Given the simple one-parameter input and no output schema, the description fully compensates by detailing return fields. It provides sufficient information for an agent to understand the tool's inputs and outputs without missing context.

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 already describes the 'id' parameter, but the description adds meaningful context by providing example formats and explaining that the id refers to a 'sealed forecast'. This additional semantic information improves parameter understanding 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 clearly states the verb 'Fetch' and the resource 'one sealed forecast', with specific id format examples (e.g., 'IA-RU-008'). This distinctively identifies the tool's purpose versus siblings like search_sealed_forecasts or get_map.

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 guidance on when to use this tool versus alternatives. For instance, it doesn't mention that if you don't have an advisory id, you should use search_sealed_forecasts first. The description implies usage only when an id is available.

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?

With no annotations provided, the description fully discloses behavioral traits: the record is append-only, values change over time, and how to independently verify using hashes and Bitcoin block heights. This level of transparency is exceptional and compensates for the lack of 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?

The description is two sentences, front-loading the primary return values and then explaining the append-only behavior and record_versions utility. It is efficient but the second sentence is dense and could be slightly tighter. Still, it 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?

Given no output schema, the description lists all return components (calibration, integrity proof, record_versions) and explains how to interpret record_versions for resolving state discrepancies. This is comprehensive for the tool's purpose and complexity.

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 input schema has zero parameters, and schema coverage is 100% (vacuously). Per the guidelines, a baseline of 4 is appropriate. The description adds no param info, which is unnecessary since there are none.

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 specifies that the tool returns corpus calibration, integrity proof, and record_versions, detailing the exact components (Brier score, manifest hash, ledger hash, etc.). This distinguishes it from sibling tools like 'get_corpus_insights' or 'get_advisory' by focusing on calibration and verifiable proofs.

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 explains that record_versions resolves discrepancies when cited states no longer match live data, guiding the user on when to use the tool to get current state and verify past states. It does not explicitly list when not to use or alternatives, but the context is clear enough for an AI agent.

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?

No annotations are provided, and the description does not disclose behavioral traits such as read-only, destructive nature, or access requirements. The cryptic language adds confusion rather than clarity.

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, poorly structured run-on sentence filled with jargon. It is not concise and does not front-load key information, making it hard to parse quickly.

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 lack of output schema and annotations, the description fails to explain the return format, usage context, or how an agent should interpret the results. It is completely inadequate for an AI agent to use effectively.

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 input schema has zero parameters, so schema coverage is trivially 100%. With no parameters to describe, the baseline score of 4 is appropriate; the description does not detract from this dimension.

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 is a dense list of internal concepts (e.g., 'mechanism ledger', 'war read') without a clear verb-resource statement. It does not specify what action the tool performs or what the output is, leaving the purpose vague.

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 on when to use this tool versus siblings like 'ask_the_record' or 'get_advisory'. The description fails to provide context for appropriate invocation.

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?

With no annotations, the description transparently discloses behavioral traits: chain-of-custody details, SHA-256 sealing, Bitcoin anchoring, confirmation of no government/PII data ingestion, and out of scope of GSA rule. Also notes it's descriptive, not a certification.

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 main purpose. Each sentence adds value, though slightly verbose. Could be trimmed without losing meaning.

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 tool with 0 parameters and no output schema, the description fully covers what the tool does and returns. Complete enough for an agent to understand.

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?

Zero parameters and 100% schema coverage. The description adds no parameter info, but baseline is 4 since schema covers and no parameters require explanation.

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 returns JYOTINT's data-handling, provenance, and governance posture, answering 'is this source safe to read/cite/ingest?'. It distinguishes from siblings by focusing on trust and compliance.

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 states 'Use for compliance / data-handling / provenance / 'can I trust this source' questions', providing clear guidance. Lacks explicit when-not-to-use but context with siblings suffices.

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?

No annotations provided, and the description does not explicitly state that the tool is read-only or disclose other behavioral traits.

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 overly verbose with a lengthy definition of IY that could be shortened, making it less concise.

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 simple input (one optional parameter) and lack of output schema, the description adequately describes what is returned, including specifics about corpus summary and domain splits.

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 adds context to the optional 'id' parameter beyond the schema, explaining it retrieves bits for a single call.

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 what the tool returns (corpus summary and optionally one call's bits), effectively conveying the purpose despite some verbose definition.

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 guidance on when to use this tool versus alternatives like get_corpus_insights or get_advisory.

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?

With no annotations, the description fully discloses behavior: computation method (92 calls, 68 events), scoring strictness, luck-prior floor, exact return fields, caveats. It is exceptionally detailed about what the tool does and returns.

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 dense and verbose, using many technical terms. It could be more concise by grouping related details or using bullet points. However, it starts with a clear main purpose sentence.

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 tool with no parameters and no output schema, the description covers all necessary context: what is computed, what is returned, and even notes caveats. It leaves no ambiguity about the tool's functionality.

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?

Input schema has zero parameters, so baseline is 4. The description adds meaningful context about the computation but does not need to explain parameters as there are none.

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 identifies the resource (corpus-level record) and action (significance test for luck). It uses specific language like 'binomial tail' and 'break-even floor' but does not explicitly differentiate from sibling tools like get_advisory or get_calibration.

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 on when to use this tool versus alternatives (e.g., ask_the_record, get_calibration_and_integrity). The description explains what it does but leaves the agent to infer the appropriate 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?

No annotations are provided, so the description carries the full burden. It explains the map is interactive, with pins containing claim, grade, probability, and a click-through. It implies a read-only, non-destructive action, and provides rich detail about the resource's 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 concise and front-loaded: it opens with the key action and resource type ('Return an EMBEDDABLE LIVE MAP'), then explains content and use case. Every sentence is necessary and no 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?

Despite no output schema and zero parameters, the description fully explains the tool's return value (a live map resource), its contents (pin details), and when to use it. It is complete for a resource-returning 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?

The input schema has zero parameters, and schema coverage is trivially 100%. Per guidelines, 0 parameters yields a baseline of 4. The description does not need to add parameter information.

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 returns an embeddable live map of the sealed-forecast corpus as an MCP-UI resource, specifying it is interactive with pins. This distinguishes it from sibling tools, none of which provide map visualization.

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 says 'Use this when a user asks to see, visualize, or explore JYOTINT's forecasts on a map.' It does not provide when-not or alternative tools, but given no sibling map tool, the guidance is clear and sufficient.

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?

No annotations present, but the description details what each call returns (claim/outcome, p, verdict, surprise_bits, 1-in-N) and mentions base rate behavior. It does not cover authorization or side effects, but as a read-only 'kit', this is sufficient.

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 detailed but slightly verbose with multiple clauses. It front-loads the purpose and efficiently packs information, though a more structured list could improve readability.

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 no output schema and the tool's complexity, the description covers the input behavior, what each call carries, and base rate outcomes. It lacks details on output format but is reasonably complete for practical use.

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 adds significant context to the single parameter 'id', explaining that omitting it yields recipes/usage/count while including it gives a specific call's row. This goes beyond the schema's minimal description.

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 provides inputs to recompute Brier, specificity, and Information Yield under custom verdicts, including stress-test recipes. It distinguishes from sibling tools like get_calibration_and_integrity which likely provide default calculations.

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 guidance on using the optional 'id' parameter (pass for one call's row, omit for recipes/usage/count). However, it does not explicitly compare to alternatives or state when not to use this tool.

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?

Discloses that the timeline is neutral, with official source first, then JYOTINT sealed call, and mentions what it does and does not establish. Since no annotations exist, this is good transparency.

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 informative without being overly long, but could be slightly more concise. It front-loads the main purpose and then adds necessary details.

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?

Despite no output schema, the description explains the response structure (official source first, then hash-anchored call) and includes what entries do and don't establish. This is sufficient for a simple single-parameter 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 100%, so baseline is 3. The description adds examples ('LA-022', 'new-glenn-ng3') and clarifies the id parameter accepts advisory id or slug, adding value beyond the schema description.

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 retrieves a 'before-the-event' or after-action timeline for a named event, using advisory id or slug. It uses specific verbs and resource, distinguishing it from siblings like get_advisory which provides the advisory text itself.

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?

Provides explicit usage: 'Use for what dated public warnings preceded [event]. Omit id to list every available timeline.' It gives context but doesn't explicitly state when not to use or mention alternatives.

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?

With no annotations, the description carries full burden for behavioral traits. It describes what is listed (sealed forecasts not yet resolved) but fails to disclose factors like authentication, pagination, or result format. The poetic phrasing adds no actionable behavioral insight.

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 sentence, which is concise. However, it includes a somewhat verbose parenthetical explanation ('anteriority you can watch') that could be simplified. It front-loads the key action and resource.

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 simplicity of the tool (no parameters, no output schema, no annotations), the description provides a basic understanding of the result set. However, it omits important context like whether results are paginated, how to interpret 'window has NOT yet resolved', and whether there are any access restrictions. It is minimally adequate but has gaps.

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 has zero parameters, and the schema coverage is trivially 100%. The description does not need to add meaning beyond the schema since there are no parameters to document. The baseline score of 4 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 clearly states that the tool lists sealed forecasts whose window hasn't resolved, using specific terms like 'sealed forecasts' and 'window has NOT yet resolved'. It effectively conveys the core purpose, though it doesn't explicitly differentiate from the sibling tool 'search_sealed_forecasts'.

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, nor are there any prerequisites or exclusions mentioned. The description assumes the agent will infer the usage context without explicit direction.

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?

Without annotations, the description bears full burden. It correctly implies a read-only operation ('Search ... returns matching records') and adds context about Bitcoin anchoring and SHA-256 hashes, but does not explicitly state safety, idempotency, or lack of side effects.

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, front-loaded with the primary purpose: first sentence defines the action and scope, second lists returned fields. 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 tool with 3 simple parameters and no output schema, the description fully covers what it does, what it returns (listing all fields), and the unique nature of the corpus (Bitcoin-anchored, dated-before-event).

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%, providing parameter details. The description adds value by specifying the fields searched ('across id, title, and the verbatim sealed claim') beyond the schema's 'free-text query' description.

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 it searches a 'sealed-forecast corpus' using free text across specific fields (id, title, claim). This verb+resource combination distinguishes it from siblings like 'ask_the_record' or 'get_advisory', which serve different purposes.

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 free-text search across sealed forecasts, but lacks explicit guidance on when to use this tool versus alternatives (e.g., 'ask_the_record' for specific records) or 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.