LocalMark Hosted Agents

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

The description adds genuinely useful context beyond the annotations by disclosing the OpenAI dependency and that no live endpoint requests are made, which reassures an agent worried about side effects. However, it is silent on why readOnlyHint is false for what reads like an analysis tool, and it never explains that the run may consume a paid task or the role of allow_model_processing. There is a mild tension between 'No live endpoint requests' and openWorldHint=true, though the OpenAI call plausibly accounts for it, so this is not a true contradiction.

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 compact sentence pair with the operative constraint ('No live endpoint requests') front-loaded at the end of the first clause. No filler, though the semicolon-joined phrasing packs two distinct ideas into one dense line.

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 six parameters, one nested object, no output schema, and a payment/trial gate, the description should explain what a 'repair' result looks like and what the billing switches do. It covers only the payload concept and leaves the agent unable to reason about cost, retries, or what it will receive back.

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% across six parameters, and the description only gestures at the payload contents ('supplied Agent Card and optional previous card'). It says nothing about request_id, force_new_task, skip_free_trial, payment_signature, or allow_model_processing, so five of six parameters carry no meaning in either the schema or the description. For a nested, billing-adjacent parameter set, this is a substantial shortfall.

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 specific verbs and resources: analyzing a supplied Agent Card plus an optional previous card, and explaining version-aware repair/diff checks. This is distinguishable from siblings like analyze_document or analyze_payment_offers by resource. It stops short of a fully crisped scope statement because 'repair checks' and 'Agent Card' are load-bearing jargon the description never unpacks.

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: passing a previous card selects diff mode, and 'No live endpoint requests' hints at an offline review scenario. There is no explicit when-to-use, when-not-to-use, or comparison to the sibling analyze_* tools, so the agent must infer selection from the resource name alone.

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 readOnly=false, openWorld=true, idempotent=false, destructive=false; the description adds real behavior: profiling happens locally, the model only explains pre-computed facts, no code is generated or executed, and authorization is required before running. One point of friction is 'no external data sources' sitting alongside openWorldHint=true, though that most plausibly refers to inputs rather than the outbound OpenAI call. It does not explain limits of 'bounded' or whether data leaves the machine for the model step.

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 tight sentences, front-loaded with the core action and followed by the authorization constraint and exclusions. Slightly jargon-heavy ('bounded', 'computed facts') but 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 tool with a nested free-form payload, six undocumented parameters, and no output schema, the description covers the intent and safety posture but not the mechanics. An agent still cannot tell what 'bounded' means numerically, whether the model step sends data off-machine, or what the response contains.

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% across six parameters, including an untyped free-form 'payload' object with additionalProperties=true. The description only hints that payload contains CSV/JSON and that authorization is required, leaving allow_model_processing, payment_signature, skip_free_trial, request_id, and force_new_task entirely unexplained in both schema and prose.

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 concrete verb and resource: 'Profile bounded CSV/JSON locally and ask OpenAI to explain computed facts.' This clearly separates it from analyze_document and analyze_payment_offers by naming the input type and the local-then-model split. It stops short of naming a sibling outright, so it is a strong 4 rather than a 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 prerequisite 'Requires explicit authorization' is useful and the CSV/JSON + 'bounded' framing implies the intended data profile. However, there is no statement of when to prefer this over analyze_document, nor any exclusion (e.g., what 'bounded' rules out), so usage must be inferred.

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 openWorldHint=true, non-idempotent, non-destructive, but the description adds genuinely new context: the free trial cadence (one per network per 30 days), the paid price and chain/payment protocol (0.05 USDC on Base via x402), and that no fetching is performed. That is the key behavioral surface for a paid remote tool; it stops short of explaining how to actually obtain a payment signature.

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 short sentences, front-loaded with purpose then constraints then cost; no filler. It reads slightly telegraphic, but 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 six undocumented parameters, a free-form nested payload, and no output schema, the description should at least outline what payload contains and how the payment/free-trial path is selected. For a paid, open-world tool, the omission of input structure and payment flow steps is a substantial 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% across six parameters, including a bare nested 'payload' object with additionalProperties. The description only implicitly touches skip_free_trial and payment_signature via the trial/pricing sentence and says nothing about payload structure, request_id, force_new_task, or allow_model_processing, leaving required input shape 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?

States a verb (analyze) and a resource (supplied text), and 'checked quote references' hints at output flavor, but 'analyze' is generic and it never distinguishes itself from the sibling analyze_data. The 'No PDF/URL fetch' clause does narrow the scope meaningfully.

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 'No PDF/URL fetch' line tells the agent when not to call this, which is real guidance. However, there is no explicit routing versus analyze_data or the other siblings, and nothing says which input shapes are acceptable besides 'supplied text'.

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 destructiveHint=false, openWorldHint=true and readOnlyHint=false, so the description's disclaimer that no wallet actions or payments occur is useful corroboration rather than new information. It does add real context that OpenAI model commentary is performed externally, consistent with openWorldHint=true. It does not, however, explain what state is changed (despite readOnlyHint=false and a force_new_task parameter), whether results are cached, or what a successful response contains.

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 short sentences with no filler, and the core action is front-loaded ahead of the safety disclaimer. The only structural weakness is that the negative constraint is compressed into a single ambiguous clause ('No paid endpoint calls, wallet actions or payment') that could be read as a read-only claim.

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 tool with six parameters including a nested free-form object, no output schema, and 0% schema description coverage, the description is far too thin. It never explains the payload structure, what the returned analysis looks like, or what the payment_signature and trial-related flags control. It does correctly convey the safety boundary, but leaves the agent unable to call the tool confidently.

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% across six parameters, including a free-form nested payload object, so the description bears the full explanatory burden and largely fails it. The phrase 'supplied x402 declarations' faintly hints at payload content, and 'OpenAI commentary' loosely relates to allow_model_processing, but payment_signature, request_id, force_new_task and skip_free_trial are never addressed. The agent must guess at the semantics of every field.

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 and resource: compare supplied x402 payment declarations against exact local amount calculations plus OpenAI commentary. That is distinguishable from the sibling tools (advise_agentops, analyze_data, analyze_document, localize_content), which are unrelated. It loses a point because 'x402 declarations' is unexplained jargon, so an agent unfamiliar with the protocol cannot fully picture the input.

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 second sentence functions as a usage guardrail by ruling out the risky adjacent actions an agent might expect from a payments tool (paid endpoint calls, wallet actions, actual payment). However, there is no positive when-to-use statement, no mention of when a different tool should be used instead, and no prerequisites such as what must be in the payload before calling.

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, openWorldHint=true and idempotentHint=false, so the agent knows this is a non-idempotent write with external effects. The description adds real value on top: it names OpenAI as the processing backend and discloses that keys/placeholders are validated (so mismatches can fail the call), plus an auth/quota gate. It stops short of describing the cost/allowance mechanics or what 'flat' means in practice.

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 short sentences, no filler, with the core action front-loaded before the prerequisites. The second sentence is tersely vague ('shared allowance') rather than wasteful, so only minor trimming would help.

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 six-parameter, nested-payload, non-idempotent, externally-billed tool with no output schema, the definition is too thin. An agent cannot tell what payment_signature or skip_free_trial do, whether re-invocation duplicates work, or what a successful response contains.

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% across six parameters, so the description carries the full explanatory burden. It only hints at the payload contract ('flat JSON strings', key/placeholder validation) while leaving request_id, force_new_task, skip_free_trial, payment_signature, and allow_model_processing (which defaults to false yet is essential for a model-backed tool) entirely 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?

States a specific verb and resource: 'Translate supplied text or flat JSON strings using OpenAI', plus a secondary behavior ('validating keys/placeholders'). It is far more specific than the name alone, though it does not relate itself to any sibling tool (siblings such as analyze_document could plausibly overlap).

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 sentence 'Explicit authorization and shared allowance required' gives a prerequisite for invocation, which is useful context. However, it never states when this tool should be chosen over alternatives, nor what happens when the allowance is exhausted or authorization is missing.

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