Stipple — Government Tenders

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

Annotations only carry readOnlyHint=true, so the description carries most transparency burden; it excels at it. It discloses anonymity for non-authenticated callers, the exact withheld fields and withheld_reason, no currency conversion, computed_at meaning, and source attribution requirements. This is far beyond generic and does not contradict the read-only hint.

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 long but well-structured: a one-line summary, then a clearly marked when-to-use block, then response contents, then caveats. The front-loading respects agent scanning. A little redundancy ('what they plan' vs 'planned procurements') is negligible.

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 two-parameter read-only tool, the description is unusually complete: it explains parameter semantics, output fields, anonymity behavior, time semantics, currency handling, and geographic coverage. The presence of an output schema lowers the burden for return-value documentation, and this description still covers it. No critical operational detail 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 has no descriptions for either parameter (0% coverage), so the description must compensate and does: it defines buyer as 'the organisation name as published' and buyer_key as coming 'from a tender's buyer, or a previous answer.' It also clarifies that either is acceptable. This is the only real documentation the parameters get.

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 opens with a plain-language statement of what the tool returns—'What a buyer has awarded, what is ending, and what they plan'—and later names the concrete result object. It distinguishes itself from siblings by framing the use case as 'a specific buyer before a bid,' which is clearly different from generic tender search tools like find_tenders.

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 explicit triggering conditions ('USE THIS WHEN someone asks about a specific buyer before a bid') with three realistic example queries. It also tells the caller which parameters to supply and where to get them, but it does not name sibling tools or state when a different tool should be used instead.

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?

Beyond the readOnlyHint annotation, the description reveals important behaviors: FREE access, anonymous callers receive everything except the incumbent's name and must relay withheld_reason as-is, confidence is a vocabulary not a score, and windows are never invented. This is substantial behavioral disclosure beyond structured 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 long but information-dense: use-case first, then parameter semantics, then output and auth caveats. No filler sentences; each paragraph earns its place given the 0% schema coverage.

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 tool with an output schema and readOnly annotation, the description covers the non-obvious behaviors, accepted value formats, output shape, and caller-specific visibility. Missing buyer and limit details are minor because their names/defaults make them self-explanatory.

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 0% schema description coverage, the description compensates well by explaining kind, jurisdiction, window_before, and q semantics. It omits buyer and limit, which are less obvious because buyer could be confused with the q field and limit's effect is only implicit in the output total.

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?

Description clearly states what the tool returns: upcoming contract expiries, planned procurements, and recurring tenders, framed as 'what may be tendered before it is.' It gives concrete user queries and distinguishes the signal category from current-tender tools, so an agent can identify the tool's job immediately.

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 'USE THIS WHEN' directive with realistic examples, which is strong selection guidance. It does not explicitly name when-not-to-use cases or alternatives such as find_tenders, though the phrase 'before it is tendered' implies the boundary against current tender search.

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?

Beyond the readOnlyHint annotation, the description discloses meaningful behavioral details: the weekly free cap, the semantic meaning of first_seen (the 'honest clock for newness'), the deliberate absence of a location filter due to data sparsity, and the caveat about coverage when results are empty. This gives the agent more than the annotation alone and prevents misleading conclusions.

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 long but front-loaded: purpose first, then usage, then parameter semantics, then return contract and caveats. Each section earns its place, and the dense parameter notes are necessary because the schema offers no descriptions. There is no filler or repetition.

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 tool has nine parameters, zero schema descriptions, and only a readOnly annotation, so the description carries a heavy burden. It covers usage guidance, key parameter semantics, output shape, and important caveats like the missing location filter. However, leaving q, source, category, and include_closed undocumented means it is not fully complete for an agent trying to precisely construct a query.

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 usefully documents jurisdiction (with the full allowed list), tier, closing_before, and first_seen_after, but it does not explain q, limit, source, category, or include_closed. This is a substantial gap: an agent still cannot fully map user intent to all nine 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 opens with a specific verb and resource: 'Search open tenders across Australia and New Zealand.' It goes further by giving concrete example queries and explicitly distinguishing itself from match_tenders, so an agent can immediately tell what this tool does and what it is not for.

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 says 'USE THIS WHEN' and then provides representative user intents. It also names the alternative match_tenders and states the condition for choosing that instead ('which of these could MY company actually bid for'), which is clear when-to-use and when-not-to-use 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 declare readOnlyHint=true, and the description adds substantial behavioral context: it is free and within a weekly cap, reads the company website, builds a capability profile, scores tenders, handles degraded mode (keyword-only ordering), and withholds some matches with a reason. It also explains how to interpret the score and gaps, going well beyond the annotation.

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 long but information-dense. It is front-loaded with purpose and usage, then covers parameters, output fields, and caveats in a logical order. Every sentence adds value, and the use of paragraphs and examples keeps it scannable.

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 (scoring, degraded mode, withheld matches) and the existence of an output schema, the description fully explains the return structure, how to present results, and what caveats to communicate. Nothing an agent needs to call and interpret this tool 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?

Schema coverage is 0% and the description explains `company_url` (plain domain is fine, it is resolved) and `example` (built-in profile, no site read), but it does not explicitly describe `jurisdiction` or `closing_before`. These are inferable from context (e.g., 'Victoria' example implies jurisdiction), but not stated, so the description only partially compensates for the missing schema descriptions.

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 verb and resource: 'Rank open tenders against what a company actually does.' It clearly distinguishes from siblings like find_tenders (which likely searches tenders) and check_document by focusing on matching to a company's capabilities.

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 explicit trigger conditions with concrete examples ('what could we bid for', 'is there anything for a civil contractor in Victoria'), and even explains the `example` mode for demonstration. It tells the agent exactly when to use this tool.

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 description goes well beyond the readOnlyHint annotation, disclosing that the tool names sources behind login walls, sources blocked by robots.txt, and sources that returned empty on the last run with reasons. It also clarifies that snapshot sources are not presented as nightly feeds, adding important caveats about data freshness.

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 front-loaded with the core purpose, followed by usage, then the return shape. It is longer than minimalist but every section (purpose, triggers, output detail) carries valuable information. A 5 would require tightening the output enumeration, but it is well-organized.

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 tool has no parameters, a readOnly annotation, and an output schema. The description fully explains the return payload (`sources[]` and `coverage`) and the per-source fields, so an agent knows exactly what to expect. No critical usage or behavioral context 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?

There are zero parameters, so the schema is empty and schema description coverage is vacuously 100%. Per the rubric, this earns the baseline 4; there is nothing for the description to add about 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?

States a specific verb ('List') and resource ('tender data sources'), then expands with exactly what is returned: each source, its permissions, and the last run's results. This clearly distinguishes it from the sibling tools find_tenders and match_tenders, which operate on tenders rather than source metadata.

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 explicitly says 'USE THIS WHEN someone asks where the data comes from, whether a particular portal is covered, or why a search came back empty.' This is clear trigger-based guidance. It doesn't explicitly name alternatives or when-not-to-use, but the sibling names make the exclusion obvious.

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