DAP Compute Market Tracker

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

Annotations already establish readOnlyHint=true and openWorldHint=false, and the description goes well past them: it names the upstream feed, the specific regions and source price lists, the monthly granularity and October 2020 floor, and — critically — that the price-per-GPU-hour figure is derived by dividing by the GPU count on the provider's spec page. It also guarantees no averaging across providers, which materially affects how the agent should interpret and present results.

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 first sentence front-loads the core definition and the source, and each subsequent clause carries real information (granularity, derived metric, filter axes). It is dense but not padded; the nested parentheticals in sentence one slightly slow parsing of the most important 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?

With no output schema present, the description usefully enumerates the returned fields — listed instance-hour price, derived GPU-hour price, each price change, and history — so an agent knows what comes back. The remaining gap is behavioural edge cases: what happens with no provider filter, and whether unlisted GPUs yield empty or all results.

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 100% and all six parameters are self-documenting, so the baseline of 3 applies. The description mostly restates the filter axes already in the schema and does not clarify the interaction between 'since'/'until' and 'history' (that the date window narrows the change history rather than the returned rows).

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 resource — the published on-demand list price for renting a GPU instance — and its provenance (AWS Price List, Azure Retail Prices). It does not name any sibling tool, so the contrast with search_compute_contracts (negotiated/contract prices) has to be inferred from the word 'list' and 'never averaged'.

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 the filtering axes ('filter by GPU, provider, instance or date range') but never says when to prefer this over search_compute_contracts or how it relates to compute_market_events. The coverage limits (us-east-1, eastus, monthly back to October 2020) implicitly define when the tool will return nothing useful, which is a partial substitute for explicit guidance.

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=true and openWorldHint=false, so safety is covered. The description adds genuinely useful behavior: results are newest-first and include future-dated events such as a pending regulator review end date. It does not mention the default limit of 25 or any pagination/truncation behavior, which matters for a list 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 compact sentences with the resource and ordering front-loaded. The trailing filter sentence is slightly redundant with the schema but still earns its place as a quick usage cue.

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?

No output schema exists, yet the description conveys ordering, inclusion of future events, and the filterable dimensions, which is most of what an agent needs. The main gap is the default result limit and any truncation behavior for a list-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?

Schema coverage is 100%, so all six parameters are already documented in the schema, making 3 the baseline. The description reinforces the date-range, event-type and contract filters and hints at upcoming_only via 'dates still to come', but adds no syntax or semantics 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?

States a specific resource (announcements, exchange filings, regulator actions on compute derivatives) with a clear verb-like listing action and ordering (newest first). The resource is distinct from siblings like compute_list_prices and search_compute_contracts, though it never names them explicitly.

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?

'Filter by date range, event type or contract' implies how to narrow results, but there is no explicit when-to-use guidance, no exclusions, and no pointer to an alternative sibling tool for related queries.

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=true and openWorldHint=false, so the safety profile is covered. The description adds real payload context the agent could not infer: DAP Standard classification, status history, redaction status of fields, and source links with URLs. It does not cover not-found/error behavior, which is the remaining 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?

A single dense sentence with the identity and scope up front, followed by the returned contents. No filler, no restatement of the title.

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 one-parameter read-only lookup with no output schema and annotations covering safety, the description supplies enough: accepted id kinds and what the response contains. Only the miss/error path is unstated, which is a minor omission.

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, but the description goes further by decoding the id namespace (ct-, ser-, ent-, ev-) and tying each prefix to a record type. That tells the agent what a valid id should look like beyond the schema's generic 'A record id from a search...' line.

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 gives a specific verb and resource ('one record in full by id') and enumerates the four record kinds by id prefix (ct-, ser-, ent-, ev-), which immediately separates this detail-fetch from the list/search siblings. An agent can tell it is a single-record retrieval, not a query.

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: fetching one record 'by id' after a search or listing is the obvious sequence, but the description never says when to prefer this over search_compute_contracts, compute_market_events or list_compute_coverage, nor that an id must already be known. The note about id provenance lives in the schema, not the description.

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 establish readOnlyHint=true and openWorldHint=false, so safety is covered; the description then adds the substantive behavioral point — that coverage is bounded by this snapshot and that absence within it is not proof of nonexistence. It also discloses the shape of what comes back (sources, last-checked times, method), which tells the agent how to weigh freshness. No mention of pagination or size, but for a zero-argument metadata call that is a minor omission.

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, zero filler: the first enumerates returned fields, the second delivers the decision-relevant caveat. Content is front-loaded and every clause 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?

With no output schema, the description carries the burden of explaining what comes back, and it does so field by field (date, counts, venues, indices, events, sources, freshness, method). Combined with the absence-of-evidence caveat, an agent has everything needed to call it and interpret the result.

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 no parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description appropriately spends its words on return content instead of inventing parameter guidance.

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 enumerates exactly what the snapshot's coverage record contains — date, contract/venue/index/event counts, sources with last-checked timestamps, and method. That verb-less but content-specific framing clearly separates it from compute_list_prices, compute_market_events and search_compute_contracts, which return market data rather than metadata about the data. It stops short of a crisp 'returns the coverage manifest for…' opener, but the resource 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?

'Use before concluding that a contract or event does not exist' gives a concrete trigger condition tied to a negative-existence inference, which is exactly the decision an agent needs help with. It does not name a sibling alternative or state when not to call it, keeping it below the top mark.

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=true and openWorldHint=false, so safety is covered. The description adds useful behavior beyond that: it returns per-contract status, settlement index, DAP Standard classification and an id usable with get_compute_record — the return shape matters here because there is no output schema. It does not mention pagination/limit behavior or result ordering.

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 resource and scope, then the facets and return content. No filler or redundant framing; every clause carries 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?

With no output schema, the description usefully summarizes what comes back and how to chain into get_compute_record, and annotations cover the read-only profile. Remaining gap is operational detail — no mention of the default/max limit of 25/100 or whether a zero-result search is possible.

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 100%, so every parameter including enums for status and settlement is already documented in structured form. The description's facet list (venue, status, index publisher, jurisdiction, settlement, name) largely restates those fields and adds no syntax or matching-behavior detail beyond what the schema provides.

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 (search) plus the exact resource: compute derivative contracts (futures and options on GPU rental and compute price indices) recorded by the Compute Market Tracker. The facet list and the pointer to get_compute_record make it clearly distinguishable from sibling tools like compute_list_prices and compute_market_events.

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?

Implicitly tells the agent this is the broad lookup tool — searchable by venue, status, index publisher, jurisdiction, settlement or name — and that get_compute_record is the drill-down for a returned id. It does not explicitly exclude or compare against the other siblings (compute_list_prices, compute_market_events, list_compute_coverage), leaving that boundary to be inferred.

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