xsignal

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

No annotations exist, so the description carries the full burden. It discloses key behaviors: abstention below confidence bar, flat fee ($0.01), tamper-evidence receipt, and that confidence is a heuristic, not a prediction. It also explains the output formats and free trial calls. Minor gaps remain for edge cases (e.g., invalid address), but the transparency is strong overall.

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 somewhat verbose (120+ words) but front-loads key information ('FLAGSHIP' and the abstain behavior). It uses all-caps for emphasis and includes an example. However, it contains redundant details (e.g., payment model repeated) that could be trimmed for better conciseness.

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?

Without an output schema, the description adequately covers return values ('gaining', 'fading', 'abstain') and the receipt. Parameter descriptions are clear, and the example aids understanding. Missing error handling details (e.g., invalid address response) prevents a perfect score.

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%, baseline 3. The description adds minimal value beyond the schema: it explains min_confidence default (0.6) and the optional question's purpose ('free-text label'). The example shows parameter usage. More detailed syntax or constraints would elevate the score.

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 a momentum verdict ('gaining' or 'fading' or 'abstain') based on an address and confidence threshold. It distinguishes itself from siblings by highlighting its unique feature of abstaining when uncertain, using the phrase 'the only x402 signal that refuses to answer (honestly) when it is not sure.'

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 is for obtaining a momentum signal with an honesty guarantee, but it does not explicitly state when to use it versus alternatives like get_signal or get_screen. The phrase 'FLAGSHIP' and the unique 'abstain' behavior offer some guidance, but no explicit when-not-to-use or alternative comparisons are provided.

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 that safety gates momentum (no green-lighting risky tokens), mentions pricing (x402-paid, $0.05, 3 free per wallet via query parameter), and includes a disclaimer ('Not financial advice'). This adds valuable context beyond the basic purpose.

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 relatively long but packed with essential information: purpose, output categories, behavior, pricing, input format, and disclaimer. It is well-structured with front-loaded main idea. Could be slightly trimmed, but the length is justified by tool complexity.

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 one input parameter, the description covers all important aspects: purpose, output categories, safety-momentum interaction, pricing, and input format. It is complete for understanding what the tool does and what it returns. Minor improvement could be adding more structure to output fields.

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% with one parameter 'addr' described as '0x Base token address'. The description repeats this info ('addr (0x Base token)') but adds no new semantic details. Baseline 3 is appropriate as schema already documents the parameter adequately.

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 function: it fuses on-chain safety and market momentum into a single recommendation. It specifies the output categories (GO, CAUTION, etc.) and answers a concrete question ('is this token safe to touch AND moving?'). This differentiates it from siblings that likely focus on individual aspects.

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 when both safety and momentum are needed, but does not explicitly state when to prefer this tool over alternatives like get_signal or get_screen. No exclusions or sibling comparisons are provided.

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 it runs preflight (safety ⊕ momentum), returns per-token verdict and summary, includes pricing ($0.10, 3 free per wallet), and notes it's not financial advice. No annotations provided, so description covers key behavioral aspects.

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?

Compact yet informative: front-loads purpose, then output, usage, pricing, input format, and disclaimer. Each sentence adds value; no 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 no output schema, describes return approach (verdict and count). Covers input limits, pricing, and intended use. Lacks detailed output format but sufficient for 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?

Schema describes parameter as array of strings up to 10 addresses. Description adds comma-separated alternative and specifies Base token addresses, enriching 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?

Clearly states it runs a batch preflight screen on up to 10 Base tokens, returning GO verdicts and a summary count. Distinguishes from sibling tools (e.g., get_preflight) by specifying batch operation and watchlist context.

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?

States usage for 'an agent screening a watchlist', implying batch token assessment. Does not explicitly exclude single-token use or mention alternatives, but the batch 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?

Discloses core behaviors: real-time, scored by virality/freshness, cited with URLs, deduped, ranked. With no annotations, this provides reasonable transparency, but missing details on rate limits, authentication (wallet mention is minimal), and whether it is read-only.

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 concise sentences covering output, input, and pricing/example. No wasted words, front-loaded with core value proposition.

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 annotations, the description adequately explains the tool's purpose and input options. Could be more detailed on return format, but overall sufficient for an agent to use 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?

Adds value over the schema by explaining the logical grouping (query vs candidates) and the pricing context. Schema coverage is 100% so baseline is 3; description provides additional semantic context, earning a 4.

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 a real-time X/social signal with scoring and citations. Describes two input modes (query vs candidates). However, does not explicitly differentiate from sibling tools like get_intent or get_screen.

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?

Explains when to use query vs candidates, but lacks guidance on when not to use this tool or mention of alternatives among siblings. Pricing is mentioned but not usage 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 full burden. It discloses the tool's fused nature, components (market flags, social posts, summary), and pricing via x402. It does not mention permissions, rate limits, or side effects, but as a read operation, the provided information 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 efficiently conveys the tool's purpose, components, benefit, and example. Every sentence adds distinct value, though it could be slightly more structured for easier scanning.

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 covers what the response contains: market flags, top social posts, and a summary. For a simple read tool with two parameters, this is sufficiently complete for an agent to understand the output.

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 value by noting that the query parameter defaults to the token symbol, a detail not in the schema description. This enhances understanding beyond the schema alone.

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 purpose: combining Base token market intel and real-time social signals into a single brief. It specifies the verb 'get', the resource 'token brief', and distinguishes from siblings by emphasizing the fused nature and saved work.

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 when a combined market and social brief is desired, mentioning it 'saves an agent the fetch-and-fuse work.' However, it does not explicitly state when not to use it or provide direct comparisons to sibling tools like get_token_intel or get_signal, leaving some ambiguity.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns market data (not trust/safety) and is a paid endpoint with free access via wallet param. It does not mention rate limits or other behaviors, but the cost and nature are well communicated.

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: three sentences covering purpose, usage, and payment. It is front-loaded with the main purpose and efficiently communicates key information without fluff.

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

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

With no output schema, the description lists the types of data returned (liquidity, volume, price, etc.) and the source (public DEX pools). This is sufficient for an agent to understand the output, though exact structure is not specified. It is nearly complete for the tool's 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?

Schema coverage is 100% with one parameter (addr) described as '0x Base token address'. The description adds context about what the address is used for and the data returned, but does not add further parameter-specific details. Baseline 3 is appropriate.

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

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

The description clearly states it provides 'base token MARKET data' and lists specific data points (liquidity, volume, price, etc.). It explicitly distinguishes itself from a trust/safety rating and mentions it's best used as input to get_token_brief, which differentiates it from sibling tools like get_token_brief.

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 'Best used as an input to get_token_brief', giving a clear use case. It also mentions the x402 payment model with cost and free wallet option. It does not explicitly state when not to use, but the alternative is implied. This provides good guidance.

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