space-intelligence

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds genuine value beyond them: a privacy constraint ('Keep the receipt private') and polling behavior ('try again later'), though it omits any note on rate limits or eventual-consistency timing.

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 retrieval purpose, then the sibling routing, then the retry rule. Every sentence carries information, though the enumerated return-item list is slightly list-heavy for a single-parameter read tool.

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

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

With no output schema, the description usefully enumerates what can be returned, and annotations carry the safety profile, so an agent has enough to call it correctly. Minor gaps remain around receipt format and polling cadence, but nothing essential 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 description coverage is 0% – receipt_id is documented only by a UUID regex pattern. The description references receipt_id and adds the semantic that it is a private credential, but does not explain the expected format or where it comes from, so it only partially compensates for the coverage gap.

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

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

The description uses a specific verb ('Retrieve') and enumerates the exact resource contents it returns (proposed scope, price offer, payment details, operator decision, research response), keyed by receipt_id. It also distinguishes itself from the sibling respond_to_research_offer by naming it and its role, so an agent can separate the read tool from the action tool without opening either 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 explicitly routes the agent: use respond_to_research_offer to confirm/correct a scope or accept/decline a quote, i.e. the when-not-this-tool condition. It also gives the retry rule ('If no response is available, try again later'), leaving nothing to inference.

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 provide some behavioral hints (readOnlyHint=false, idempotentHint=false, destructiveHint=false, openWorldHint=false), but the description adds valuable context: acceptance records a choice, no work starts until payment, nothing owed until payment, quote must be unexpired, and a privacy warning against contact details. This goes beyond the 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 dense and front-loads the receipt_id requirement, but it's a bit of a wall of text with multiple conditional clauses. It could be structured with bullet points for clarity, though all sentences carry necessary 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 complexity (4 params, nested objects, oneOf schema, no output schema, no annotations beyond basic hints), the description covers the essential workflow: pre-check via check_research_status, action-specific requirements, and post-acceptance effects. It could mention what happens after an action or response format, but it's largely complete.

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 the meaning and requirements of each action (confirm_scope, correct_scope, accept_quote, decline_quote), the need for receipt_id, when correction text is required, and that budget is a counter-offer. This meaningfully clarifies how parameters interact beyond the raw schema 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 states a clear verb and resource: responding to SNTL's offer using a receipt_id, with four enumerated actions. However, it doesn't explicitly differentiate from siblings beyond mentioning check_research_status as a prerequisite, not as an alternative.

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 provides usage context: 'Use check_research_status before responding,' and explains the four actions and their requirements. It lacks explicit when-to-use vs. alternative guidance, though no direct alternative for responding exists.

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

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

Annotations only declare the safety profile (non-read-only, non-idempotent, closed-world, non-destructive); the description adds substantial behavioral detail beyond that: per-product pricing, automatic acceptance/decline, fixed-price quote on acceptance, delivery windows of 7/14 days, 'Nothing is owed until payment,' and the receipt/status flow. It never warns that repeat submissions are not idempotent and may create duplicates, which is the notable gap.

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

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

The core action is front-loaded and almost every clause carries weight (pricing, SLA, payment terms, receipt, privacy notice). The pricing parentheticals ('€5 to 31 December 2026, then €10') make the middle dense and slightly hard to parse, but there is little outright filler.

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

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

For a 10-parameter, nested-input submission tool with no output schema, the description covers the business workflow well but leaves the input side largely undocumented and does not describe what the immediate response contains beyond 'accepted or declined.' An agent can call it, but cannot confidently fill most fields from the description.

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 only 20% across 10 parameters, so the description must compensate, yet it only elaborates on the product enum (answer/brief/map) with prices and page counts. It says nothing about subjectType, companyName, budget, topics, outputFormat distinctions, maximumAgeDays, or consentToStore, leaving most of the input surface unexplained.

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 opening states a specific verb and resource: 'Ask SNTL one research question about a space company or market, and choose the product.' It also positions the tool in a workflow by naming check_research_status as the follow-up. It does not distinguish itself from the other sibling, respond_to_research_offer, so it falls short of a clean 5.

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

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

The description gives clear usage context: one question, choose a product, accepted or declined automatically, and explicitly says to 'Keep the receipt and return with check_research_status.' It also imposes a content restriction ('Do not include contact details or personal information'). It stops short of stating when not to use it or how it relates to respond_to_research_offer.

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