304NotModified

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the external-lookup, non-mutating nature is partly covered. The description adds that answers are verified and carry confidence and expiration, plus a no-personal-data caution for context, but does not elaborate on latency, source freshness, or failure 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?

Purpose is front-loaded in the first sentence, followed by the domain value list and the context note. The long domain enumeration is functional rather than filler, though the whole is slightly dense.

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

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

An output schema exists, so return values need not be re-explained, yet the description helpfully previews them. With domain values and context documented, an agent has enough to call the tool correctly despite the 0% schema coverage.

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, and it does: it enumerates the accepted domain values and explains what context is for (the current task, without personal data). Only 'question' is left to common sense, which is reasonable.

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

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

States a specific verb (pose une question) and resource (question factuelle), and even summarizes the returned artifact (réponse vérifiée avec sources, confiance, expiration, request_id). The purpose is clear, but there is no explicit differentiation from the sibling tools calculate and feedback.

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 word 'factuelle' implicitly scopes usage to factual questions needing verified answers, which is useful direction. However, there is no statement of when to prefer this over calculate or feedback, and no exclusions or prerequisites are given.

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 mark this readOnly and idempotent, so the safety bar is lower. The description still adds meaningful context beyond them: the calculation is deterministic, 304 supplies no market data (you must pass your own candles), the result contains the published method/values/timestamp, and it is not investment advice.

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 the core purpose, then mode definitions, then the params format, then the return/disclaimer note. Dense but every sentence carries information; no redundant restatement of the schema.

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

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

An output schema exists so return values need not be described in depth, and the description still sketches the result. It covers the deterministic/privacy framing, the enum, and a params example, leaving only per-calculation parameter detail as a gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden. It maps the 'calculation' enum to concrete meanings and shows a 'params' example with the candle object shape (time/open/high/low/close/volume), plus a pointer to /llms.txt. But it only illustrates one of the three calculations' bodies and does not specify the params each mode requires, leaving gaps for a schema with open nested objects.

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

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

States a specific verb and resource ('Calcul déterministe sur VOS bougies') and enumerates the exact three calculation modes (ichimoku-rvol, regime, position-size), each glossed. An agent can distinguish this computational tool from the sibling 'ask'/'feedback' tools immediately.

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 what each calculation mode produces (Ichimoku confirmed by relative volume; ADX trend/ATR volatility/direction; position size for a fixed risk), which gives clear context for choosing a mode. However it never states when to prefer this tool over the 'ask' sibling, so no explicit alternatives or exclusions are given.

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=false and idempotentHint=false, so the write/non-idempotent nature is known. The description adds genuine context beyond that: no key/authentication is needed and 'Pas de données personnelles' warns against personal data. It stops short of describing what happens after submission or any 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 purpose and target are front-loaded, followed by inline parameter glosses and a privacy note. The content-hint list is a bit dense but each clause maps to intended message content, so little is wasted.

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

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

For a simple two-parameter write tool with annotations covering safety and an output schema covering returns, the description supplies the missing pieces: parameter meanings, the optional flag, the no-auth note, and the no-personal-data caveat. Adequate and coherent.

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 carry the burden, and it does: 'message' is defined as the user's text and 'looking_for' as the sought information/service, correctly flagged as optional ('facultatif'). This meaningfully compensates for the undocumented schema, though it adds no format or length constraints.

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 action (leaving a free-form message) and an explicit target (the owner of 304NotModified), so the purpose is unambiguous. It does not, however, differentiate itself from close siblings like 'feedback' or 'ask', which an agent would need in order to choose between them.

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

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

Usage is only implied: 'sans clé ni question préalable' hints that no prior context is required, and the content hints (what you searched for, what was missing, why you're leaving, a suggestion) frame the intended input. No explicit when-to-use-vs-alternatives guidance or exclusion against 'ask'/'feedback' is given.

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

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

Annotations declare readOnlyHint=false and idempotentHint=true, so mutation and repeat-safety are already covered. The description adds useful semantics for the issue field and notes optionality of two params, but doesn't state permission requirements or the effect of sending feedback on downstream data. This is adequate additional context but not rich.

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 and front-loaded, opening with the core purpose before parameter notes. The long enumeration of issue values is necessary for semantics but contributes to density. No filler sentences.

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 an output schema exists, return values need not be described. With zero schema description coverage, the description supplies the missing parameter semantics and links to the ask tool. It is nearly complete, lacking only any note on permissions or consequences of submitting feedback.

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. It explains request_id refers to a prior « ask » response id, useful is true/false, and enumerates all seven issue enum values with glosses, plus optionality of issue and comment. This meaningfully adds to the bare schema, though comment could be slightly more specific.

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 tied to a specific upstream tool: telling whether a response obtained with « ask » was useful. It clearly connects to its sibling ask and is distinguishable from calculate. It does not explicitly name a verb like 'submit feedback', but the intent is unambiguous.

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

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

It clarifies this operates on responses from a specific sibling tool (« ask ») and requires the request_id from that response. It does not discuss timing or when not to send feedback, but the contextual link to ask is strong guidance for 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?

Annotations give readOnlyHint and idempotentHint, but the description adds real behavior beyond them: the auth constraint ('seule la clé qui a passé la commande peut la suivre'), the expected latency (several hours), and the billing rule (failed/expired states are not billed). It does not discuss rate limiting for polling beyond 'de temps en temps', which keeps it short of a 5.

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

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

One dense paragraph, front-loaded with purpose then parameter meaning then state semantics then polling advice. Every sentence carries information, though the parenthetical status list is compact and slightly run-on rather than crisply structured.

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 an output schema present, the description need not explain return values, yet it still summarizes the meaningful states and the auth/timing constraints an agent needs to poll correctly and interpret results. Nothing required for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must carry parameter meaning and it does: run_id is defined as the identifier returned by run_service, which is the single most important thing an agent needs for this one required param. The status values enumerated are return-state semantics rather than parameter semantics, so they do not count here.

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

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

States a specific verb ('suivre') and resource ('commande asynchrone passée avec run_service'), and names the sibling run_service that creates the thing being followed. An agent can distinguish this from run_service (submit) and list_services (enumerate) without opening any schema.

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 says when to use it (following a command created by run_service), how (poll 'de temps en temps', with the reason that work takes hours), and gives an exclusion: only the key that placed the command may follow it. That is when/when-not/alternative coverage.

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 and idempotentHint, so safety is covered. The description still adds genuinely non-structured operational context: that some services run in async mode and can take several hours, and that each entry carries price, delay and limits — useful for setting agent expectations about latency and cost.

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 catalogue scope and the async/latency caveat, then the read-before-use rule. The middle enumeration of per-item fields is somewhat enumerative but each item signals decision-relevant data (price, delay, limits).

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 an output schema present, the description need not restate return fields, yet it does list them — mildly redundant but harmless. Combined with the sibling-routing instruction, nothing an agent needs in order to call this zero-parameter read correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to clarify beyond confirming the catalogue is unfiltered.

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

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

States a specific verb+resource ("Catalogue des services") and immediately scopes it against the closest sibling by noting it covers services "au-delà des questions" (i.e., not the ask tool). It also names the concrete example autark-static-site, so an agent knows exactly what class of offering lives here.

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?

Ends with an explicit ordering instruction: "Lire avant quote_service ou run_service." That names the alternatives and the condition under which this tool must be consulted first — no inference required.

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 only say readOnlyHint=false and idempotentHint=false. The description adds critical behavior not in annotations: the quote is free, the price is firm, it expires after a few minutes, and it can be used only once. These are exactly the operational details an agent needs before relying on it.

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

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

The description is front-loaded with the key promise and constraints, then briefly annotates the two parameters. Every phrase carries information, with no filler or repetition.

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

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

Because an output schema exists, return details need not be covered. The description does well on behavior and next-step integration, but it is weak on the required nested params object, which is a meaningful completeness gap for a tool taking arbitrary per-service inputs.

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 should clarify both parameters. It gives a useful example for service ('fr-suppliers') but only says params are 'selon input_schema', while the schema itself provides no property descriptions and allows arbitrary nested content. The required params object remains semantically opaque.

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 the operation clearly as obtaining a free, firm-price quote for a service, and it explicitly distinguishes this from run_service by saying the quote is usable once with run_service via quote_id. An agent can tell what it creates and how it relates to the sibling tool without opening the schema.

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

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

It states the quote is valid for a few minutes and usable only once with run_service (quote_id), which clearly frames this as a pre-execution step. It does not explicitly say when not to use it or name all alternatives, but the context for calling it before run_service is strong.

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 relying on annotations, it discloses billing semantics (charged only if status=completed for sync, only on delivery for async), idempotency behavior (same result, no double billing via request_key), budget enforcement (nothing executes beyond max_price_eur), required API key, and the async status=queued + run_id lifecycle. This is rich operational context well beyond readOnlyHint=false and openWorldHint=true.

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 the core action and return, then parameter notes, then the sync/async billing rules. Dense but each sentence carries information; minor redundancy in restating billing twice ('facturé seulement si…' / 'Facturé seulement à la livraison').

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 high-complexity, billable, async-capable tool with an output schema present, the description covers billing, idempotency, auth, and async tracking adequately. The remaining gap is guidance on what belongs in 'params' and which 'service' values are valid, which the sibling list_services would presumably supply.

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 carries the burden. It meaningfully explains max_price_eur, quote_id, and request_key, but says nothing about the two required parameters 'service' (which services are valid) or the free-form nested 'params' object, leaving 2 of 5 parameters undocumented in both schema and 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?

Starts with a specific verb+resource ('Exécute un service') and states what it returns (structured result with sources, limits, missing items). It also distinguishes two operating modes (sync vs async) and names the sibling get_run for async follow-up, though it does not differentiate itself from quote_service or list_services.

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

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

It routes the agent conditionally: sync returns immediately, async returns a run_id 'suivez-le avec get_run'. It also tells the agent to reuse request_key on retry. However, it never states when to call run_service versus the quote_service/list_services siblings, so the choice among alternatives is left implicit.

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