world-sense

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

With no annotations, the description bears full responsibility for behavioral disclosure. It explains the tool provides observed data (not predictive) and suggests verifying staleness. It also details the data components (volume, tone indices, escalation stage). While it does not cover auth needs or rate limits, these are less critical for a read-only data retrieval tool with no parameters.

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, concise and front-loaded. The first sentence states the purpose and key data elements; the second clarifies non-predictive nature and suggests staleness check. No unnecessary 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 zero-parameter tool without output schema, the description covers the main data returned (indices, escalation stage, country pairs) and freshness check. However, it does not specify which seven country pairs or the exact format/range of indices, leaving some ambiguity for an AI agent without 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 tool has zero parameters, so schema coverage is trivially 100%. The description adds meaning by explaining what the tool returns, which is sufficient given no parameters need 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 clearly states it provides observed bilateral signal-intensity (volume, tone, escalation stage) for seven tracked country pairs. It uses the verb 'observed', which implies retrieval, and distinguishes itself from predictive tools. However, it does not explicitly use an action verb like 'retrieves' or 'lists', and does not differentiate from sibling tools like arcane_deltas or arcane_overview.

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 indicates this tool is for observed intensity data, not predictions, giving context on when to use it. It also advises 'Check as_of/stale' to ensure freshness. However, it does not explicitly state when not to use it or mention alternative sibling tools for other purposes.

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 discloses that the tool does not forecast or trade, but fails to describe any behavioral traits such as output format, latency, or data freshness. The description is insufficient for an agent to understand the tool's side effects or constraints.

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 (two sentences) but the first sentence is cryptic and could be clearer. It is front-loaded with key concepts, but the phrasing 'What... serves and what it explicitly does NOT serve' is awkward.

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 parameters and no output schema, the description is incomplete. It does not explain what 'per-stream validation notes' are, nor what the output format looks like. An agent would have insufficient context to use the tool 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?

With 0 parameters and schema coverage of 100%, the baseline is 4. The description adds meaning by explaining that the tool serves capability info and per-stream validation notes, which goes beyond the empty schema.

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

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

The description states the tool provides information about what ARCANE's World-Sense serves and does not serve, plus validation notes. However, it lacks a clear action verb (e.g., 'get' or 'list') and the phrasing is cryptic, making it unclear what the tool returns when invoked.

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 mentions what the tool does not do (forecast, advise, trade), providing some exclusionary guidance, but does not specify when to use this tool over its siblings (e.g., arcane_domain, arcane_overview). No explicit when-to-use or alternatives are stated.

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 discloses that only 'observed levels' are provided and that 'some senses go silent when their baseline saturates', which is useful behavior. However, with no annotations, it fails to explicitly state read-only nature or other important traits like idempotency or data freshness 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?

The description is concise, consisting of two sentences. It is front-loaded with the core purpose and efficiently adds a behavioral caveat in the second sentence, with no redundant 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?

Given no output schema and no parameters, the description adequately covers the tool's purpose, data types, and an important behavior (silent senses). It could be more specific about response format, but overall provides sufficient 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?

There are no parameters, so schema coverage is 100%. The description adds no parameter meaning, but the baseline of 4 is appropriate as per guidelines for zero-parameter tools.

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 'latest observations from ARCANE's primary-source physical senses' with listed examples. It distinguishes the tool's scope from siblings by specifying 'primary-source physical senses', though it does not explicitly differentiate from each 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?

No guidance is provided on when to use this tool versus alternatives. The only instruction is to 'Check as_of/stale', which is vague and does not help in selecting among 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?

With no annotations, the description carries full burden; it explains that grounding-sense items fire once then go quiet, and that the tool shows only observed diffs. This gives sufficient behavioral insight for a read-only, state-diff tool.

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 efficient sentences, front-loaded with core purpose, and no superfluous 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?

Given zero parameters and no output schema, the description adequately covers purpose and behavioral nuances; however, some domain jargon (e.g., 'grounding-sense') may assume prior knowledge.

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 is empty with 100% coverage; description adds value by explaining what the tool returns (diffs) and caveats, which is meaningful context beyond the bare 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?

Description clearly specifies verb ('what changed') and resource ('ARCANE domains and primary-source senses'), with the qualifier 'observed diffs only' distinguishing it from siblings like arcane_domain which may return full state.

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 guidance on interpretation (absence of grounding-sense items is not calm) and advises to check 'as_of/stale', but does not explicitly state when to prefer this tool over 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?

With no annotations provided, the description carries the full burden. It discloses the tool's non-predictive nature ('ARCANE NOTICES the present; it does not predict') and clarifies that news coverage is about unusualness, not truth or importance. This provides adequate behavioral context for a read-only drill-down tool.

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 three sentences, each earning its place: first sentence states purpose and outputs, second adds behavioral caveat, third provides usage instruction. No wasted words, front-loaded with key 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?

Given the tool's simplicity (one parameter, no output schema), the description covers purpose, outputs, behavioral nuance, and staleness check. It is complete enough for an agent to select and invoke correctly, though it could optionally describe return structure or error cases.

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 100% coverage, but the description adds meaning by explaining what the 'domain' parameter selects (drill-down for that domain) and what outputs it produces. This goes beyond the schema's simple 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 verb 'drill-down' and the resource 'domain', and lists specific outputs (risk/momentum series, regime posterior, news-coverage theme cards). It distinguishes from siblings by focusing on a single domain, though it could explicitly contrast with sibling tools like 'arcane_overview'.

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 mentions the tool is for present observations and not predictions, and advises to 'check as_of/stale'. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention prerequisites 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.

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

No annotations provided, but description explicitly states it does not predict or advise, and notes temporal nature ('as observed now') and need to check staleness. Sufficiently transparent for a read-only snapshot tool.

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 purpose, no wasted words. Efficient and clear.

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 zero parameters, no output schema, and no annotations, the description covers purpose, limitations (no prediction), and usage note (staleness). Could mention output format, but not essential.

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?

No parameters in input schema, so baseline 4 applies. Description adds no param info, which is acceptable as no parameters exist.

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?

Clearly states it provides current overview including Combined Threat Score, per-domain risk rows, cascade state, and cross-domain gauges. Differentiates from siblings by noting it does not predict or advise.

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?

Implies usage by stating 'ARCANE NOTICES the present' and advises checking staleness, but no explicit guidance on when to use this tool vs alternatives like arcane_domain or arcane_deltas.

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 carries the full burden. It transparently states the tool is a reference for design information, clarifies that weights are design config not fitted parameters, and advises checking staleness. This provides behavioral context beyond a simple listing.

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 with zero wasted words. The first sentence immediately conveys the core purpose, and the second adds crucial nuance. Highly efficient and front-loaded.

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 zero-parameter, read-only reference tool, the description is fully complete. It explains what the tool exposes, the nature of its data, and a practical usage note (checking staleness). No gaps are evident.

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?

No parameters in the schema, so baseline is 4 per guidelines. The description adds no parameter-specific semantics, but also doesn't need to 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 explains the tool's purpose: detailing the composition of the Combined Threat Score, including roll-ups, premiums, design weights, and provenance tags. It distinguishes itself from sibling tools (e.g., arcane_overview, arcane_domain) by focusing specifically on the score tree decomposition.

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 implicitly suggests usage for understanding score composition and checking freshness via 'as_of/stale', but lacks explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, but given sibling tools, the context helps differentiate.

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, so description carries full burden. Describes returned fields (push time, source as_of, stale flag) and purpose, adequately disclosing behavior for a read-only tool.

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, fully front-loaded with purpose and usage hint. Every word earns its place; no extraneous content.

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?

Complete for a zero-parameter tool with no output schema: explains what it returns and when to use it. No gaps given the 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?

No parameters (0 params, 100% schema coverage), baseline 4 applies. Description adds no extra parameter info, but none is needed.

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?

Description clearly states the tool provides freshness info (push time, source as_of, stale flag) for all public ARCANE keys, and distinguishes from sibling tools that focus on other aspects like capabilities or data streams.

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 instructs to call this before treating any reading as current, providing clear when-to-use context. No when-not-to-use given, but the simplicity of the tool makes it unnecessary.

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. It discloses the tool's non-forecast nature, live state view, and specific data points. It does not mention side effects, but the tool appears read-only. No contradictions with annotations.

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

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

The description is concise but packs essential information. It front-loads the core purpose and adds clarifying details. Minor redundancy (e.g., 'NOT a forecast' repeated) could be trimmed.

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 tool without an output schema, the description fully explains what data is returned (N/M completion, direction, staleness, fork checkpoints) and hints at output format. It compensates for lack of structured output 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?

The input schema has zero parameters, so the description does not need to explain them. It would benefit from clarifying that there are no filters or required inputs.

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 defines the tool's purpose as a live scenario tracker showing completion, direction, staleness, and fork checkpoints. It distinguishes itself from a forecast and implies differentiation from sibling tools like 'arcane_overview' by emphasizing real-time state data.

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

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

The description explicitly states this is NOT a forecast and advises checking 'as_of/stale' for freshness. It provides clear context for when to use it (for current state) but does not explicitly mention when not to use or alternatives, though the sibling list offers 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?

With no annotations, the description carries the full burden. It clearly states the tool is 'descriptive state only, not a forecast', which sets expectations for non-predictive behavior. It also mentions the repair date and live status, adding transparency about data limitations. No contradiction with annotations as none exist.

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 long, efficiently conveying the tool's purpose, scope, and a usage hint. It front-loads key information ('Observed multi-stage trigger-chain state') and avoids redundancy. Minor improvement would be more bullet-like structure, but current form is clear and 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 tool has no parameters, no output schema, and no annotations, the description adequately covers what the tool returns (state for five domains), its nature (descriptive), and a critical usage note (staleness check). It does not list the exact domains or explain z-scores, but the level of detail is appropriate for a simple stateless 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?

There are zero parameters, and the input schema coverage is 100%. The baseline for 0 parameters is 4, and the description adds no parameter info (none needed). The description does not need to elaborate further as no parameters exist.

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 multi-stage trigger-chain state for five domains, including stage activation, z-scores, and chain health. It distinguishes itself from a forecast by explicitly saying 'Descriptive state only, not a forecast'. However, it does not explicitly differentiate from sibling tools like 'arcane_score_tree' or 'arcane_system_status', though the context implies a unique focus on chain state.

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 advises to 'Check as_of/stale', indicating the importance of timestamp freshness. It also notes the chains were repaired and not yet exercised live, guiding users about data relevance. However, it does not explicitly state when to use this tool over alternatives, nor does it provide exclusions or prerequisites.

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