Veridion Disclosures

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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the bar is low. The description adds genuinely useful behavioral context beyond that: the counts are live and measured from serving views, and they should supersede cached figures, which tells the agent about freshness and authority of the data.

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, both earning their place: the first defines the payload and its source, the second states the precedence rule. The most decision-relevant content is front-loaded 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 zero-parameter tool with an output schema, the description needs only to say what is returned and any caveats; it does both by enumerating the counts and flagging their live/authoritative nature. Nothing required to call or interpret it 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 there is no parameter semantics to document; the baseline for a no-parameter tool is 4. Nothing in the description misleads about inputs, and the absence of parameters is consistent with a pure read of aggregate coverage.

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 resource (live coverage counts) and enumerates the exact metrics returned (rows, filers, per-source totals), plus the data source (serving views). It is unambiguous about what the tool produces, though it does not explicitly contrast itself with siblings like get_status or get_disclosure_history.

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?

"Prefer these numbers over any cached figure" gives a clear selection rule for when this tool's output should be trusted over other sources. It stops short of naming alternative tools or stating when not to use it, so it is strong context rather than full when/when-not 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 cover the safety profile (readOnly, idempotent, closed-world, non-destructive), yet the description adds real behavioral context: the stream is append-only, amendments supersede rather than overwrite, both before/after versions persist, each with its own change block and receipt.url. That predicts the shape and completeness of results in a way annotations cannot.

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 what the tool returns and in what order, followed by the append/amend model. Dense but mostly load-bearing; the 'never why' clause is more interpretive guidance than tool behavior, though it is short.

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, return values need not be re-explained, and the description still characterizes the version chain and restatement semantics. An agent has what it needs to call this correctly and read the 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?

There is only one parameter and schema description coverage is 100%, including the fact that identifiers survive restatement and are never reused. The description adds no further syntax or format detail for disclosure_id, so the baseline of 3 applies.

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 and verb-equivalent action: every observed version of one disclosure, returned oldest first. It is clearly distinguishable from search_disclosures (which finds disclosures) and from the other siblings (coverage, status, members).

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 — you need a disclosure_id (from search_disclosures, per the schema) to trace its history — but the description never states when to prefer this over search_disclosures or when it is not applicable. The 'restated=true' and 'report what changed and when, never why' lines guide interpretation rather than tool selection.

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 cover the safety profile (readOnly, idempotent, non-destructive), and the description goes well beyond them: it discloses that the endpoint self-downgrades when its own arithmetic detects staleness and "never guesses green," and it explains what degraded_reasons, sources[].index_reconciliation and bulk_export.merkle_root actually mean. That is exactly the kind of trust/verification context an agent cannot get from 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?

Front-loaded with the one-line purpose, then detail in descending priority, ending on the actionable precondition. It is dense with domain jargon (merkle_root, index_reconciliation) but every sentence carries information; it is not padded.

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 the description is not obliged to enumerate return fields, yet it still explains the semantics of the most consequential ones (degraded states and their causes, index reconciliation, the daily commitment). Combined with full annotation coverage and no parameters, nothing an agent needs in order to call this 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 there is nothing for the description to disambiguate and the baseline is 4. No parameter-level guidance is needed 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?

The opening line names a specific resource and scope — source freshness plus bulk-snapshot health — so an agent knows this is a health/status read rather than a data-retrieval call. It does not explicitly distinguish itself from the sibling get_coverage, which is the one tool an agent might plausibly confuse it with, so it stops short of 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?

"Check it before trusting a large pull" gives a concrete precondition for calling the tool, which is real usage guidance. There is no explicit when-not or named alternative (e.g. get_coverage), so it is clear context without full routing.

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 readOnly/idempotent/non-open-world, so the safety profile is covered. The description adds genuinely useful behavior beyond that: executive-branch filers return null with an explanation and identifiers are never invented, which sets expectations for partial results. It stops short of rate limits or pagination, so not 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?

Three tight sentences, front-loaded with the core behavior and edge case, then filtering modes, then the recommended resolution sequence. Every sentence carries distinct information with no redundancy.

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 and the annotations are rich, so return formatting and safety need not be repeated. For a 3-param, 0-required lookup tool, the purpose, edge-case null behavior, filtering semantics, and resolution workflow are all present.

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 parameter meaning is already fully documented (substring name, Bioguide example, exact member_id). The description largely restates the same semantics plus a resolution order, adding little that isn't already in the schema; baseline 3 applies.

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 action (list filers with official identity) and clearly scopes the population (congressional filers carry Bioguide IDs; executive-branch filers return null). An agent understands what it returns. It does not differentiate from siblings, though none of the listed siblings genuinely overlap, so a 4 rather than 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?

Gives an explicit resolution workflow: 'Resolve a person with name first, then confirm with the returned member_id or bioguide,' and enumerates the three filtering modes. It provides clear context but does not state when to prefer this over an alternative tool, nor any exclusions.

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 cover safety (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds real behavioral context beyond them: every row resolves to a citable government PDF via receipt.url, and as_of guarantees no look-ahead bias. It does not discuss rate limits or result-size behavior, keeping it at a 4.

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?

Roughly five dense sentences, front-loaded with the core purpose before the filtering/pagination mechanics. Nearly every clause carries information, though the receipt.url citation instruction is a soft nudge rather than strictly necessary.

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 explained, yet the description still surfaces the two most important output affordances (receipt.url for citation, page.next_cursor for pagination). Combined with the 9-parameter surface fully covered, an agent has everything needed to call this correctly.

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 a baseline of 3 applies, but the description adds meaning: chamber='executive' is where the President's disclosures live, as_of yields observed-on-or-before rows without look-ahead bias, and updated_since drives change polling. These clarify intent rather than just restating the schema, warranting a 4.

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') and resource ('receipt-linked US government financial disclosures') and immediately scopes the corpus (both chambers under the STOCK Act plus executive-branch OGE filings). It also distinguishes itself from the sibling list_members by naming it as the resolver for member_id.

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 concrete routing conditions: chamber='executive' for OGE/President filings, as_of for point-in-time reconstruction, updated_since for change polling, and next_cursor for pagination. It does not explicitly say when NOT to use this tool or name alternative search siblings, so it stops short of full when/when-not guidance.

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