Glasser

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

Annotations already declare readOnlyHint and destructiveHint false. The description adds useful context beyond annotations by explaining that 'held' is reserved by in-flight runs and by noting this endpoint also serves as a cheap key probe. 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 one efficient, front-loaded sentence followed by a docs link. Every phrase earns its place: the currency, the three balance components, the in-flight reservation clarification, and the key-probe behavior.

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 low-complexity, read-only tool with no output schema, the description covers the main return fields and purpose. The phrase 'cheapest probe that the key works' is slightly awkward and could be clearer, but it does not prevent an agent from understanding how to use the 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?

The tool has zero parameters, and schema description coverage is 100%, so the baseline for parameter semantics is 4. The description adds no parameter-specific details, but none are needed given the absence of parameters.

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 retrieves the workspace's balance in USD and explicitly names the returned components: balance, held, and available. It also adds a distinct secondary purpose (cheapest key-working probe), making it easy to distinguish from siblings like inspect or search.

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 intended use is clear: check the workspace balance and verify the API key works. It does not explicitly mention when not to use it or compare against sibling tools, but the context is self-evident enough for a simple read-only balance check.

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 readOnlyHint and destructiveHint annotations already establish that this is a safe, non-destructive operation. The description adds valuable behavioral nuance beyond annotations: selecting an endpoint_version does not lock Price, new Runs use the current Price at admission, and task_id is used to record the inspection against the same piece of work.

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 compact and front-loaded: the first sentence states the core contract, and the following sentences add necessary workflow and pricing caveats. The docs URL is a minor addition but not wasteful.

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?

The description provides enough context for a read-only pre-run inspection tool: it says when to call it, what it returns, and how it relates to run and search. There is no output schema, so its explicit enumeration of returned fields helps. A concrete example or error behavior would improve completeness slightly.

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 schema description coverage at 0%, the description must compensate, and it does for the two non-obvious parameters: task_id should come from a search and is used for recording, and endpoint_version can be selected without locking price. It does not explain provider and endpoint formats, but their schema patterns and names are largely self-explanatory.

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 verb ('Get') and a precise resource ('one endpoint's execution contract') and enumerates exactly what is returned: provider-native input schema, exact price with charge clauses, endpoint_version, run mode, and timeout. This clearly distinguishes inspect from sibling tools like run or search.

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 an explicit when-to-use rule: 'Always inspect before the first run of an endpoint.' It also connects to sibling tools by instructing the agent to pass endpoint_version to run and task_id from search. It does not explicitly state when not to use the tool, but the guidance is strongly contextual.

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 destructive/idempotent/openWorld, and the description adds substantial context beyond them: billing per published price, idempotency_key reuse semantics with replayed:true, the counterintuitive rule that a provider 404/500 is a COMPLETED run carried in provider_response, and run_url being members-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?

Dense but front-loaded: capability and charge first, then idempotency, then error/async semantics, then safety guardrails, then run_url citation. Every sentence carries a distinct operational rule; nothing is 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?

There is no output schema, so the description compensates by describing return fields (replayed, provider_response, run_url) and the async polling path. For a destructive, billable, open-world call it covers safety, cost, idempotency and follow-up actions completely.

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 reported at 0% (only task_id and endpoint_version carry inline descriptions), so the description must carry weight. It explains idempotency_key generation/reuse and points input construction at the inspected input_schema, but leaves provider and endpoint format unstated beyond their patterns.

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?

Opens with a specific verb+resource+consequence: 'Execute one endpoint and charge the workspace per its published price.' It also implicitly differentiates from siblings by routing async polling to runs_get, so an agent can tell it apart without reading schemas.

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?

Explicit when-to-use and when-not: poll runs_get for QUEUED/RUNNING results, and 'never run speculatively, in loops or in bulk without naming the price and getting the user's go-ahead.' It also defers to the user's own keys/integrations over Glasser, giving a clear precedence rule.

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, destructiveHint=false, openWorldHint=false, so safety is covered; the description goes further by disclosing domain behavior the annotations cannot: status and charge are independent (a FAILED run can carry a non-zero charge), run_url resolves to provider-returned records in the workspace console, access is 'members only', and citation of run_url is required because the run id alone opens nothing. That is substantive added context on auth and result semantics.

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 returned fields, followed by the two non-obvious behavioral facts (failed-but-charged, cite run_url), then a docs link. Dense and every clause carries information; no 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?

With no output schema, the description takes on the burden of enumerating return fields and does so explicitly. Combined with the read-only annotations, an agent has everything needed to call this correctly and interpret the result, including the citation requirement.

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 schema gives only the type/format (uuid pattern) without prose. The description partially compensates by naming the parameter's role ('by run_id') and clarifying that the id alone opens nothing, but it never explains where a run_id comes from or its expected form. Marginal value over the structured fields.

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 ('Get one run by run_id') and enumerates exactly what comes back (status, output, provider_response, failure, charge_usd, charge_basis, run_url), which is enough to distinguish it from runs_list (plural/summary) and runs_stop (mutating). An agent can identify the 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?

Usage is implied: fetch a single run when you already hold a run_id ('Get one run by run_id'). There is no explicit routing guidance telling the agent to use runs_list or search first to obtain a run_id, and no when-not condition. Adequate but inferential rather than explicit.

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 destructiveHint=false, so safety is covered. The description adds valuable behavioral context: cursor-paginated, newest-first ordering, and exact-match semantics for the task filter. This goes beyond what annotations provide and helps the agent understand the tool's 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?

The description is a single, dense sentence that front-loads the core action and filtering capabilities, then adds pagination and a docs link. No fluff or repetition; every clause adds value.

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 read-only list tool with optional filters and no output schema, the description covers essential invocation details: scope, ordering, filtering options, pagination, and a specific hint about using task_id from search. The only missing detail (e.g., default limit) is available in the schema, and the docs link provides further reference. The description is complete for correct usage.

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 description coverage is 0%, meaning the description must compensate for explaining parameters. It names the filterable fields (status, provider, endpoint, task) and clarifies task uses exact match. It also mentions cursor-paginated, implying cursor/limit usage. However, it does not explain the expected formats (e.g., status enum values, endpoint/provider patterns) or the limit's default/max, leaving some gaps. The schema itself provides descriptions only for task, so partial compensation.

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 (List) and the resource (this workspace's runs), and specifies ordering (newest first). It distinguishes from siblings like runs_get (single run) and run (likely starting a run) by framing this as the list operation. The scope (workspace) is explicit.

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 provides clear context on when to use this tool: to list multiple runs with optional filters. It gives a specific usage hint for the task filter (use a task_id from a search), which guides correct invocation. However, it does not explicitly state when not to use it or mention alternatives by name, though the sibling list implies a distinction.

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 indicate destructive and idempotent behavior, but the description adds crucial context: pre-dispatch runs become STOPPED and free, while dispatched runs settle normally and are charged. The guarantee that 'paid-for work is never discarded' is exactly the kind of behavioral nuance an agent needs.

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 terse, information-dense sentences: the action, the critical lifecycle nuance, and a documentation link. Every sentence earns its place with no 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 one-parameter action with annotations covering safety and idempotency, the description covers the lifecycle and billing implications well. It does not describe the response or error cases, but no output schema exists and the operation is simple, so this is a minor 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%, and the description does not mention run_id at all. The parameter name and schema format/pattern are helpful, but the description provides no additional meaning and fails to compensate for the complete lack of parameter 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 the action ('Request a stop') and the resource ('an in-flight run'), making it distinct from sibling tools like runs_get and runs_list. The scope is precise without ambiguity.

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 clear context on when to use the tool: for in-flight runs before dispatch, and explains behavioral differences after dispatch. It does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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 as a safe read, and the description adds substantial behavior beyond that: default page size of 5, limit cap of 20, `total`/`next_cursor` pagination, the meaning and limits of `score` (cosine similarity, not a verdict, absence is not proven), and the task_id threading contract. This is rich, non-obvious context an agent could not infer.

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 fairly long, but it is front-loaded with the purpose before pagination and scoring caveats, and every sentence carries operational meaning. Slightly verbose, but nothing is 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?

With no output schema and low schema coverage, the description fully covers return shape (provider, endpoint, price, run mode, score, total, next_cursor, task_id) and the semantics needed to use results correctly. 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 only 20%, but the description compensates for nearly every parameter: limit default and max, cursor/next_cursor usage, task_id threading across later calls, and the required use_case. Query is only implied by 'by keyword', a minor gap in an otherwise complete compensation.

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 ('Search Glasser's data sources — runnable paid API endpoints — by keyword') and names the sibling actions it feeds into ('inspect and run'). An agent can distinguish it from balance, inspect, and run without opening a 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?

Gives clear context: compare price across providers, try other words on empty results, and inspect before running. It does not explicitly state when-not to use it or which sibling to prefer for lookups, but routing to inspect/run is implied by 'inspect before running'.

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