INITE Atlas

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description is free to add provenance detail — double-reading each change from vendor page or registry, and refusing to attribute user-typed corrections to the vendor. That is genuine behavioral context about data trustworthiness beyond 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 core purpose, then two short sentences on data quality. Slightly folksy phrasing ('a correction somebody typed in'), but every sentence carries information rather than 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?

An output schema exists, so return values need not be explained, and the description even hints at denominator semantics ('how many tools were in a position to change at all'). Complete for a one-optional-param read feed, with the only real gap being sibling disambiguation.

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% and the single 'days' parameter is already documented in the schema ('How far back, default 30'). The description adds nothing about the lookback window, so the 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 concrete verb+resource (what changed among tools in the INITE Atlas) and enumerates the change types — price, free plan, OpenAPI spec, MCP listing. It does not, however, differentiate itself from the near-identical sibling atlas_dataset_changes, which an agent could easily pick by mistake.

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: a time-windowed change feed for monitoring vendor tool movement. There is no explicit when-to-use, when-not-to-use, or pointer to an alternative such as atlas_dataset_changes or atlas_search, so the agent must infer the routing decision.

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 cover safety (readOnly/idempotent/non-destructive); the description adds far more: results are computed without a model from verified vendor pricing pages, 'unknown is never shown as missing or free', nothing is saved, and there is a rate limit of sixty per day per address. That is substantial disclosure beyond the structured fields.

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-loads the core action and packs a lot into a compact block, with no filler sentences. It is dense rather than wasteful, though the return-value detail is slightly long given an output schema exists.

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 comparison tool with an output schema and full safety annotations, the description covers the remaining unknowns an agent needs: determinism, rate limit, non-persistence, and how unresolved plans are represented. 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 coverage is only 25%, so the description must carry more weight; it maps 'seats, minutes a month, required capabilities' to the scenario fields and implies the 2-5 tool count, but says nothing about billing, currency, or longestRecording. It partially compensates for the coverage gap but leaves documented-by-neither 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 concrete verb and resource ('Preview a price comparison of 2-5 Atlas tools for a usage scenario') and narrows scope to the first category, AI transcription. It is instantly distinguishable from the dataset/publish siblings it lives among.

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?

Explicitly frames itself as a non-persistent preview and routes persistence to atlas_dataset_create, and the schema adds 'resolve names with atlas_search first'. It gives clear context but no explicit when-not-to-use conditions beyond the persistence split.

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 cover the safety profile (readOnlyHint/openWorldHint/idempotentHint/destructiveHint), so the description adds substantial new context: the provenance of each record (stated by a domain-verified owner), its freshness semantics (carries the last-confirmation day, which should be quoted), and a hard constraint that INITE does not run checkouts. That is exactly the kind of behavioral detail annotations cannot express.

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 purpose, then provenance, then the critical caution. Every sentence earns its place with no filler or repetition of structured fields.

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-value description is unnecessary. For a one-parameter read tool the description covers purpose, optional filtering, data provenance/freshness, and a representation caution, leaving nothing an agent needs in order to call and use it 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 description coverage is 100% and the single 'domain' parameter already carries an example ('elevenlabs.io'). The description only restates that the filter is optional and limited to one domain, adding little meaning beyond the schema, so the 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?

The description states a specific verb+resource ('Live discount codes for AI tools in the INITE Atlas') and scope ('optionally for one domain'), which is credibly distinct from the owner_* siblings. It never explicitly names an alternative tool, so differentiation relies on the reader inferring the read-vs-owner-write split from the names.

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 (retrieve all codes, or narrow to one domain) but there is no explicit when-to-use or when-not-to-use guidance and no routing to siblings. The 'never call verified' line constrains downstream wording rather than telling the agent when to pick 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?

Beyond the annotations (destructiveHint, idempotentHint, openWorldHint), the description discloses the post-condition (API answers 410 with a fallback line), irreversibility ('already-downloaded snapshots cannot be recalled'), and the auth contract including the 401-with-OAuth-fallback behavior. That is exactly the kind of operational context annotations cannot carry.

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?

Four sentences with the core action front-loaded, followed by consequences then the auth requirement. Mostly lean, though the 'degrades instead of breaking' clause is mildly narrative and could be tighter.

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 no prose, and the safety profile is well covered by annotations plus the irreversibility and auth notes. The gap is expectedConfigVersion: what happens on a version conflict for a destructive, concurrency-guarded call is left unstated, which could cost an agent a failed or misjudged invocation.

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 33%: only idempotencyKey is documented. expectedConfigVersion is an optimistic-concurrency token whose mismatch behavior is not explained anywhere, and datasetId gets only vague ownership framing ('a dataset the account owns'). For a destructive tool, the description does not compensate for the undocumented 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 verb+resource are specific and concrete: 'Stop serving a dataset the account owns' clearly names the action and target, even though it never uses the word 'archive' from the title. It does not explicitly distinguish itself from atlas_dataset_update or atlas_dataset_publish, so an agent must infer the difference among siblings.

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 effect and intent ('a page that still reads it degrades instead of breaking') and states a prerequisite (signed-in inite.ai account) plus the guest failure path (401 + OAuth). However, it never says when to choose this over atlas_dataset_update or a soft-delete sibling, so the alternative-selection guidance is only implied.

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 the read-only, idempotent, non-destructive, closed-world profile, so safety is covered. The description adds ordering ("newest first"), a pagination cursor mechanism, and the qualifier "confirmed" changes, but does not explain what confirmation means or whether historical revisions remain queryable.

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?

One sentence, purpose first, paging instruction second — nothing superfluous. The middle clause ("plans added, removed, or which fields moved") is slightly compressed and reads awkwardly, which keeps it short of a 5.

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 described, and the description covers purpose, ordering, and pagination. Remaining gaps — what "confirmed" means and auth requirements — are minor for a read-only tool with a required datasetId.

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 carries the burden. It does explain `after` as a revision number used for paging, adding real meaning over a bare integer, but says nothing about `datasetId` beyond the name. Roughly half the parameters get semantic support.

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+resource: surfacing confirmed changes between revisions of a published dataset, with the kind of change enumerated (plans added/removed, fields moved). It is distinguishable from atlas_dataset_get and atlas_dataset_update, though it never names a sibling to sharpen the contrast against atlas_changes, which sounds adjacent.

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 by the paging instruction ("Page with `after`"), which tells the agent how to iterate but not when this tool is the right choice over atlas_dataset_get or atlas_changes. No exclusions or prerequisites are stated.

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 cover idempotency and non-destructiveness, and the description adds real context beyond them: the resource is created private/draft and is not public until atlas_dataset_publish, the response includes dataset id, configVersion and a coverage preview, and unauthenticated calls fail with 401 plus an OAuth flow. It does not discuss rate limits or what happens on validation failure, 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?

Front-loads the core action and scope, then adds return shape, publication state, and auth in short clauses. Dense but every sentence carries information; minor overlap between the return-value sentence and the existing output schema.

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 spelled out, and the auth flow is well covered. However, with a deeply nested config object and only 20% schema description coverage, the description leaves the shape of config, category and lang largely unexplained for a creation tool with three required parameters.

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% across 5 parameters, so the description must compensate. It loosely maps 'tools', 'required capabilities' and 'default scenario' to the config object, but says nothing about title constraints, category, lang, or idempotencyKey beyond what the schema already documents. Partial compensation only.

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 ('Save a comparison as a private draft dataset in the signed-in account') and names the configurable payload (tools, required capabilities, default scenario). It also explicitly contrasts with atlas_dataset_publish, so an agent can separate this create-draft step from the publish step without opening either 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: use this to persist a comparison as a draft, and publication is deferred to atlas_dataset_publish. It also states the auth precondition (signed-in inite.ai account, guest calls 401 and trigger OAuth). No explicit 'when not to use' versus atlas_dataset_update, which keeps it from 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 establish readOnly/idempotent/non-destructive, so the safety bar is met elsewhere. The description adds genuinely new behavior: the authorization boundary (owner-only drafts) and the fact that supplying revision switches the call to a history read rather than a current-state read.

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?

One sentence, front-loaded with the verb and resource, with parentheticals enumerating returned fields rather than padding. Dense but every clause carries information; the parenthetical nesting is slightly hard to parse on first read.

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 tool with an output schema, the access rules and revision semantics are the only things an agent must know, and both are present. Return values are additionally described despite the output schema existing, so nothing material 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 0%, so the description carries the burden. It explains the non-obvious parameter, revision, as triggering a history read, which is real added meaning; datasetId is self-evident from the tool name. It does not explain revision format or which value means latest, so not a 5.

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?

Names a specific verb (Read) and resource (dataset), then spells out what is returned in each access case: a published snapshot with freshness and default result, or a draft's config/configVersion/preview. That content-level detail cleanly separates it from atlas_dataset_create/update/publish/archive siblings.

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?

States an implicit when-not condition: drafts are readable 'only by its owner', while published datasets are readable by anybody. That tells the agent when the call will succeed. It never names a sibling alternative or an explicit exclusion, so it falls 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?

Adds a lot beyond the annotations: the exact acceptance rules (HTML must carry the data plus a visible link, not in a comment/iframe/noscript), daily re-check cadence, that state surfaces via atlas_dataset_get, that nothing on the page itself is changed, and the auth requirement (guest call returns 401 and starts OAuth). These are exactly the facts an agent cannot get from readOnlyHint/openWorldHint.

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?

Purpose is front-loaded and every sentence carries weight (acceptance rules, cadence, state location, auth). The construction 'Tell the Atlas ... , and check it now:' is slightly dense 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?

With an output schema present, return values need not be explained, and the description covers auth, semantics, cadence, and where state lives. What is missing is only the explicit datasetId/url parameter mapping.

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?

At 50% schema coverage, datasetId has no schema description, but the narrative implies it is the published dataset while url is the deployed page. That mapping is inferable but not stated explicitly, so the description only marginally compensates for the coverage gap.

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?

Specific verb+resource: it registers which public page shows a published dataset and immediately verifies it. It also partly distinguishes the reading path by pointing to atlas_dataset_get for state. The dual nature (register + check) is clear, though the title 'Check where a dataset is shown' underplays the write side.

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 ('Tell the Atlas which public page shows a published dataset, and check it now') and it routes state-reading to atlas_dataset_get, but there is no explicit when-not guidance or stated alternative for registering vs. verifying. Adequate but leaves selection inference to the agent.

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 write (readOnlyHint=false), openWorld, idempotent and non-destructive. The description adds real context beyond them: an immutable revision is created, specific URLs and install notes are returned, auth is required and guests get 401 with an OAuth redirect. It stops short of saying what happens to any prior published revision or on an expectedConfigVersion mismatch.

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 sentences, front-loaded with the action and its effect, then conditions, then auth. No filler; every clause carries operational 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?

An output schema exists, so the return values need not be explained in detail (they are mentioned helpfully anyway). Prerequisites, auth behavior and the call condition are all present. The remaining gap is the semantics of expectedConfigVersion as a concurrency guard, which neither schema nor description nails down.

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 only 33% – only idempotencyKey is documented. The description hints that expectedConfigVersion names the version being published, but does not explain that it acts as a guard or what a mismatch does, and datasetId is never clarified. Partial compensation for a real coverage gap.

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?

Specific verb and resource: 'Make the named configVersion of a dataset public: cuts an immutable revision.' The phrase 'cuts an immutable revision' and the returned artifact list (public API, page and compare URLs, install notes) clearly separate this from siblings like atlas_dataset_update or atlas_dataset_archive.

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 gating: 'Call it only when the user asked for a public comparison' states a when-not condition, plus a prerequisite ('at least two tools with verified plans') and an auth condition ('signed-in inite.ai account: a guest call answers 401 and starts the OAuth flow'). Nothing about invocation eligibility is left to inference.

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 cover safety (readOnlyHint=false, idempotentHint=true, destructiveHint=false), and the description adds substantial context beyond them: optimistic concurrency via the read configVersion, the VERSION_CONFLICT outcome on a stale version, the deferred effect on a published dataset, and the 401/OAuth behavior for guest callers.

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 dense sentences, front-loaded with what changes, followed by concurrency and publish semantics, then auth. No filler, though the third sentence's OAuth detail is somewhat tangential to the change operation itself.

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, and the description covers concurrency, publish interplay, and auth. The main gap is that the nested config fields (tools, capabilities, default scenario) are never tied back to the patch structure.

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 only 25% schema description coverage, the description must compensate, and it does for expectedConfigVersion ('Names the configVersion it read'). It also names the updatable concepts, though 'tools, required capabilities, default scenario' are not mapped to the nested config object, leaving that sub-structure opaque.

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 (change) and resource (dataset the account owns) and enumerates the mutable fields: title, language, tools, required capabilities, default scenario. It also distinguishes itself from atlas_dataset_publish by noting the published set serves its published config until that sibling runs.

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?

Clearly positions the tool against atlas_dataset_publish ('keeps serving its published config until... publish') and states the auth condition that gates use. It stops short of explicit when-not guidance or naming other siblings such as atlas_dataset_create or atlas_dataset_get.

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, idempotentHint and destructiveHint=false, so safety is covered. The description adds real behavioral context beyond them: every fact is dated, and 'claimed' vs 'found' data are kept distinct, which tells the agent how to interpret the returned records.

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 lookup subject is front-loaded, which is good, but the rest is one long run-on clause enumerating field categories (price, docs, MCP, status page, certifications) that the output schema already defines. Those clauses rarely earn their 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 one fully described parameter, annotations covering safety, and an output schema present, the description need not explain return values. The added note about dating and claimed/found separation rounds it out; only the missing routing guidance against siblings leaves a 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 coverage is 100% and the single parameter is fully documented with examples ('elevenlabs.io' / 'ElevenLabs'). The description's 'by domain or name' merely restates the schema, so the 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?

The description states a specific verb+resource ('One AI tool from the INITE Atlas, by domain or name') and enumerates the record contents, so an agent can tell it apart from atlas_search and atlas_compare. It is clear but verbose, and the sibling differentiation is implicit rather than stated.

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 by 'one AI tool ... by domain or name' — the natural reading is 'use for a single known tool', but there is no explicit when-to-use, no exclusion, and no pointer to atlas_search or atlas_compare as alternatives.

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-destructive, closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: a signed-in inite.ai account is mandatory, and a guest call returns 401 and triggers the OAuth flow. It does not add rate-limit or pagination behavior, which is the main 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?

Two sentences, each earning its place: the first enumerates returned fields, the second handles the auth precondition. Front-loaded with the resource description. Slightly dense with the colon-separated field list, but no wasted prose.

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-value detail need not be spelled out, and the description still summarizes the payload. The auth requirement is disclosed. What remains thin is the absence of any sibling differentiation among the many atlas_owner_* tools, which is the one thing an agent might still need.

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 the baseline is 4 per the rubric. There is nothing for the description to clarify beyond what the empty schema already conveys, and it does not introduce any confusing parameter-like phrasing.

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 and scope: 'The tools the signed-in account has claimed in the INITE Atlas', listing exactly the fields returned (verification status, badge link liveness, premium expiry, card address). That is far more concrete than a tautology. It does not, however, explicitly distinguish itself from sibling tools like atlas_owner_stats or atlas_owner_card that also concern the signed-in owner's data.

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 — an agent can infer this lists the caller's own claimed tools, but there is no explicit 'use this when…' or routing to alternatives such as atlas_owner_stats or atlas_owner_card. The auth condition (signed-in required, guest → 401) is stated, which is helpful context but not a when-to-use guideline.

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?

With readOnlyHint/idempotentHint/destructiveHint already covering the safety profile, the description adds genuine behavioral context: it requires a signed-in account, a guest call returns 401 and triggers the OAuth flow, and it explains that empty card lines come with remediation advice. It does not cover pagination or the exact response shape, hence 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?

Two sentences with no filler, and the auth note is front-loaded in the second position. However the first sentence is a dense dash-laden clause chain ('what the card prints ... - price, hiring, releases, company - with the page ... and what to do about each empty line') that is hard to parse and would benefit from restructuring.

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 single-param, read-only tool whose annotations cover safety, the description is largely sufficient: it explains what fields are reported, that each is tied to a source page, how empty lines are handled, and the auth prerequisite. Without an output schema it could be more explicit about the returned structure, but the substantive gaps are minor.

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% for the single 'domain' parameter, so the schema already carries the meaning ('the tool's domain as the Atlas lists it, e.g. acme.ai'). The description adds nothing about the parameter, so the baseline 3 is correct.

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 (prints/shows) and resource (the Atlas card of a claimed tool) and enumerates the fields involved (price, hiring, releases, company, claim status, premium). It is clear what the tool returns, though it never names or contrasts itself with near siblings like atlas_owner_stats, so it stops short of full differentiation.

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 context is implied rather than stated: it says the tool applies 'for a tool the account has claimed' and 'needs a signed-in inite.ai account', which scopes the caller, but there is no explicit when-to-use/when-not guidance or named alternative among the many atlas_owner_* siblings.

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 cover the safety profile (idempotent, non-destructive), but the description adds substantial context they don't carry: the three proof mechanisms with snippets, the instant-proof email condition, the required follow-up tool, and the 401/OAuth behavior for guest calls. That is exactly the kind of behavioral disclosure structured fields cannot express.

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 tightly packed sentences, each doing distinct work: what happens, what comes back and why, and the auth/next-step constraints. 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?

There is no output schema, so the description correctly describes the return (three proof methods with exact snippets). Auth requirements, idempotent resume behavior, and the required follow-up call are all covered, leaving nothing an agent needs before invoking it.

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 the single domain parameter is already documented in the schema, so baseline is 3. The description adds no formatting or normalization 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?

"Start (or resume) a claim on a tool's Atlas card for the signed-in account" gives a precise verb+resource+scope. It is clearly distinct from siblings like atlas_owner_verify (the follow-up) and atlas_owner_release (the undo).

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?

Explicitly routes the agent forward ("Then call atlas_owner_verify") and states the fast path condition (verified email on the domain proves at once). It gives clear context but no explicit when-not-to-use or statement of prerequisites beyond the sign-in requirement.

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?

Goes well beyond the annotations (which only flag non-readonly/non-destructive/non-idempotent): it discloses lifecycle behavior (coupon stops showing unless confirmed every 45 days), publication surface (card + Atlas feed), and auth behavior (guest call returns 401 and starts OAuth). Rich, non-redundant context.

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 action and single dense but purposeful sentences; each clause carries information (fields, expiry, auth). Minor awkwardness in 'proved owner' phrasing slightly hurts readability but not size.

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 still communicates the resulting state (published on card/feed, expires without reconfirmation) and the auth path for a 2-param nested-object tool. AppliesTo/terms/startsAt remain unaddressed, a small 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 coverage is 50% with a 12-property nested coupon object undocumented in the schema, and the description compensates by explaining title format, endsAt ISO/within-a-year constraint, url meaning, and the kind alternatives (code/percentOff/amountOff+currency/trialDays). It leaves terms, startsAt and appliesTo unexplained, so not a full 5.

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+resource (publish a discount on the card and Atlas coupon feed) and is clearly distinct from the sibling list/confirm tools (atlas_owner_coupons, atlas_owner_coupon_set). An agent can tell what this creates 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?

Gives the prerequisite ('For a proved owner') and names the alternative for the maintenance cycle (atlas_owner_coupon_set, every 45 days). It does not explicitly contrast create-vs-update semantics against the sibling set/coupons tools, 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.

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

Annotations already mark this read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely non-structured behavior: the auth failure mode (401 triggering an OAuth flow) and the fact that non-live coupons are included, which an agent could not learn from the schema. Pagination and result-size behavior remain undisclosed.

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 front-loaded sentence delivers the result set, its completeness (

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 list tool with no output schema, the description covers what is returned, why the ids matter, and the auth gate. It leaves return shape/pagination implicit, which is a minor rather than blocking 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?

There is a single parameter (domain) with 100% schema description coverage, so the schema already carries the meaning and the baseline is 3. The description's "this claim" phrasing loosely points at the domain-scoped lookup but never names or clarifies the domain argument, adding no syntax or format detail.

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 concretely scopes the resource: "the coupons this claim has published, live or not" including draft/inactive ones, and it supplies the ids for a named sibling consumer (atlas_owner_coupon_set). It does not, however, distinguish itself from atlas_coupons or atlas_owner_coupon_add, so an agent must infer the ownership boundary from the name alone.

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 states the precondition for calling (a signed-in inite.ai account; guests get 401 and enter OAuth), and it routes the agent forward by saying the returned ids feed atlas_owner_coupon_set. There is no explicit when-not or alternative-listing guidance, so it falls 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 cover the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, openWorldHint=false), and the description adds genuinely new context: the 45-day confirmation decay window and the 401/OAuth behavior for guest callers. Minor tension exists between "withdraw takes it down" and destructiveHint=false, but the idempotent/status-toggle framing makes this a soft state change rather than 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?

Two tight sentences with zero filler; the action semantics come first and the auth caveat second. Every clause carries information an agent needs.

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 3-parameter mutation tool with annotations but no output schema, the description covers the two hardest points (action meaning, auth failure mode). It stops short of explaining couponId or what a successful response returns, but nothing critical 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 only 33% (only domain is documented). The description does compensate for the action enum by explaining both values' meaning, which is real added value, but couponId is left completely undocumented in both schema and description — no format, source, or how to obtain it.

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 concrete verb pair and resource: "confirm" marks a coupon as still valid, "withdraw" removes it. An agent understands exactly what the tool changes, though it never explicitly distinguishes itself from siblings like atlas_owner_coupon_add or atlas_coupons.

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 gives a clear condition for each action (confirm = still works, withdraw = take it down) and states the auth prerequisite up front. What's missing is routing guidance against the sibling coupon tools (e.g. when to use this vs atlas_owner_coupon_add).

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-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavior: a guest call returns 401 and triggers the OAuth flow, and payment is a browser-side action rather than a tool side-effect.

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?

It is short and front-loads the return value before the payment/auth caveats, but the second clause of the first sentence ('ninety-day stats with the shelf beside the card') is cryptic filler that costs comprehension.

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 one parameter, no output schema, and annotations carrying the safety profile, the description supplies the missing pieces an agent needs: what is returned (premium details plus a payment link) and the auth/401 behavior. Only the premium feature list remains elliptical.

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 a single parameter with 100% schema description coverage, so the schema fully documents 'domain'. The description adds no further meaning about the parameter, making the baseline 3 appropriate.

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 does convey that the tool returns what premium adds and the payment link for the card owner, but the phrasing is jargon-heavy ('ninety-day stats with the shelf beside the card') and never states a clean verb+resource. It does not clearly distinguish itself from near siblings like atlas_owner_card or atlas_owner_stats.

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 gives a concrete exclusion — checkout is a card form in a browser, not an agent action — which tells the agent this tool surfaces a link rather than performing payment. It also states the signed-in account requirement and the 401/OAuth guest behavior, though it names no explicit alternative sibling.

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 only readOnlyHint=false and destructiveHint=false; the description adds the human-review gate ('a person at INITE reviews before it shows') and precise auth behavior ('a guest call answers 401 and starts the OAuth flow'). These are behavioral traits the annotations cannot convey and are exactly what an agent needs to set expectations on latency and failure.

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 verb and purpose, and nearly every clause carries payload (field mappings, exclusions, auth). The field list makes it dense and slightly run-on, but there is no filler sentence.

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 thin schema coverage, the description supplies the missing pieces: editable fields, review-gated result, auth behavior, and a faster alternative. An agent could invoke it correctly, though the return/confirmation shape after submission remains unstated.

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%, so the description must carry the load, and it does: it maps each enum value to its companion parameter ('name' with name, 'pricing' with a nested {model, freeTier, startsAt{amount,currency,per}|null,source} object, 'note' with free text). It does not document the required 'domain' beyond the schema's own description, keeping it just short of a 5.

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 (propose a correction) and resource (your card), then enumerates the exact editable fields (name, pricing, note) and explicitly excludes the one-line description and verdicts. An agent can distinguish it from sibling tools like atlas_owner_set_read_pages without opening any 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?

Names an alternative route (set_read_pages is the faster way to a price) and states exclusion conditions (description/verdicts not editable), plus an auth prerequisite. What's missing is explicit framing of when a proposal is preferable to just setting read pages, but the routing signal is present.

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 establish the mutation/safety profile (destructive=true, idempotent=true), and the description goes well beyond them: it enumerates exactly what is destroyed (owner mark, coupons, owner tools), what survives (the card itself), and what the caller must do afterwards (a fresh proof for a later claim). It also discloses the auth behavior on unauthenticated calls (401 plus OAuth flow), which no annotation conveys.

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 the action and its side effects, followed by the consequence and the auth prerequisite. No filler, no repetition of name or 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 single-parameter destructive mutation with no output schema, the description covers the action, what is destroyed and preserved, the follow-up implication, and authentication behavior. An agent has everything needed to decide and to call it correctly; return shape is not required since there is no output schema.

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% for the single 'domain' parameter, so the schema already documents format and an example ('acme.ai'). The description adds nothing about the parameter, so the baseline 3 for fully-covered schemas 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?

The opening sentence gives a specific verb and resource ('Give up the claim on a card'), and the follow-up explicitly separates this from a card deletion by stating the card stays in the Atlas. It is clear what the tool does, though it never names the natural counterpart (atlas_owner_claim) or any other sibling explicitly to anchor the distinction.

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 a prerequisite ('Needs a signed-in inite.ai account: a guest call answers 401 and starts the OAuth flow') and a consequence ('A later claim needs a fresh proof'), which is useful context. However it never states when an agent should release a claim versus not, only what the call requires and what follows.

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?

Adds substantial behavior beyond the annotations: rate limits (weekly free / hourly premium) and the auth flow (guest call returns 401 and kicks off OAuth). These operational details are exactly what the structured fields cannot convey and directly affect whether/how an agent invokes it.

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: purpose first, then cadence limits, then auth. No filler, and the most decision-relevant information is front-loaded.

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 is the sole source of return-value context, and it does say what facets get re-measured. It omits whether the read is synchronous or asynchronous and what the response shape is, leaving a minor gap for a mutation-triggering, non-idempotent call.

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 a single parameter with 100% schema description coverage, so the schema already documents 'domain' as the Atlas-listed domain. The description's 'claimed site' and 'pages you named' hint at the domain's relationship to the ownership claim, but add no syntax or format detail beyond 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?

The description gives a specific verb ('Re-read the claimed site now') and enumerates exactly what is captured - activity, hiring, releases, crawler policy, identity files. It is clear what the tool does, though it does not explicitly contrast itself with close siblings like atlas_owner_verify, atlas_owner_stats, or analyze_site.

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 implies usage ('now', plus weekly/hourly cadence tied to tier) and states the auth prerequisite, but names no alternative tool and gives no when-not-to-use guidance. An agent can infer this is the forced-fresh read path, but must deduce it from siblings.

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?

Goes well beyond the annotations: it discloses that the Atlas applies its own validation guards (price must be printed on the page, job boards must be your own, release notes need dates), states read-timing (new pricing page within the hour, careers/releases on the next atlas_owner_remeasure read), and warns that omitted entries are cleared. The auth failure mode (401 + OAuth) is also stated.

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 dense sentences, front-loaded with what to send; every clause carries information (targets, guards, timing, auth). Slightly compressed prose and a 'proved owner' phrasing add mild parsing friction, but there is 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 4-parameter mutation with no output schema and non-destructive/idempotent annotations, the description covers targets, validation expectations, replacement semantics, timing, and auth. What it omits is response shape and how validation failures are surfaced, which is a minor gap given no output schema exists.

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 already 100%, but the description still adds semantics the schema lacks: what content each URL must satisfy (printed price, own job board, dated entries) and the whole-payload replacement rule. This meaningfully augments parameter interpretation rather than restating field names.

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 concrete verb+resource: telling the Atlas (owner tooling) which three page types on your own domain it should read. It also implicitly separates itself from atlas_owner_remeasure by describing what that sibling does with the pages. It stops short of an explicit 'use this instead of X' framing, but an agent can identify the operation.

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 gives real operating context: all three URLs must be sent each call because an omitted one is cleared, and it requires a signed-in inite.ai account (guest call returns 401 and starts OAuth). It does not spell out when to prefer this over atlas_owner_propose_edit or atlas_owner_verify, so 'alternatives' guidance is partial.

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-destructive/closed-world, so the safety profile is covered. The description adds genuine value on top: the tier-dependent window (30 vs 90 days) and the auth behavior ('a guest call answers 401 and starts the OAuth flow'). It stops short of return format/pagination detail, 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?

It is compact at roughly three sentences and front-loads what is returned, but the ornamental phrasing ('the shelf beside it', 'its neighbours on the shelf') spends words on metaphor rather than on semantics, slightly hurting legibility.

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 does the job of describing returns (views, clicks, impressions, top queries) along with tier windows and auth requirements. For a single-param read tool this is close to complete, though it omits pagination/response-shape specifics.

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 there is a single 'domain' parameter, so the schema already documents it fully. The description adds nothing about the domain argument (format, matching, case), so the 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?

It states the resource clearly: card views, click-throughs, plus Google impressions/clicks/top queries. The purpose (owner-facing card analytics) is decipherable, but the metaphorical phrasing ('the shelf beside it') and the absence of a clean verb mean it never contrasts itself against siblings like atlas_owner_card or atlas_my_listings.

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 - it signals that this returns your card's performance and that it requires an inite.ai account, but it never states when to call this versus atlas_owner_card or atlas_owner_premium explicitly. The tier split (free=30 days, premium=90 days) hints at context but isn't framed as a selection condition.

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 openWorldHint, idempotentHint and destructiveHint=false, but the description adds genuinely new behavior: the signed-in-account requirement, that a guest call returns 401 and kicks off the OAuth flow, and that the answer is either "verified" or a description of what was missing. That is meaningful context beyond the structured fields.

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, purpose front-loaded, with the auth caveat trailing. The parenthetical method explanations are dense but every clause carries information; nothing is padding.

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 3-parameter tool with no output schema, the description covers the methods, the auth prerequisite, and the shape of the response ("verified, or what was missing"), which is what an agent needs to call it correctly. Only minor gaps remain (e.g., what a successful verification does to the claim's state).

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 67%, and the description meaningfully disambiguates the enum by explaining each method's mechanism (badge link on a page, homepage meta tag, TXT record) and the role of pageUrl. This adds real semantic value beyond the bare enum values.

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+resource ("Check the proof placed for a claim") and enumerates the three verification methods, so an agent knows exactly what the tool does. It does not, however, name or contrast itself with the nearby siblings (atlas_owner_claim, atlas_owner_card), so it stops short of full sibling differentiation.

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 clarifies the method choices (badge/meta/dns) and the auth prerequisite, which implies when a call is valid, but it never states when to reach for this tool versus atlas_owner_claim or atlas_owner_card. Usage is inferable 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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so credit goes to what the description adds: the default sort ('measured use'), the AND semantics of slices ('must all hold'), and the fact that calls are free with no allowance consumed. It stops short of describing pagination or result shape.

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 and dense, with the mechanics explained in the first clause. However, the verbatim re-listing of 28 categories and 13 slices duplicates the schema enums, adding bulk the agent could have obtained from structured fields.

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 no explanation, and the description covers filtering semantics, default sort and cost. It is slightly incomplete on pagination (limit/offset) and on the undocumented 'liked' sort value, but is otherwise sufficient for correct invocation.

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 only 33% (q and slices are documented; sort, limit, offset and category are not). The description partially compensates by explaining filter combination and sort order, but it omits the 'liked' sort option present in the enum and says nothing about limit/offset for paging. The long category and slice enumerations largely duplicate the schema enums rather than adding meaning.

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: filter the INITE Atlas catalogue by phrase, category and slices. The phrase 'without a model' implicitly contrasts it with the model-driven sibling match_tools, so an agent can distinguish the two, though it never names the alternative.

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 rather than stated: 'without a model' signals deterministic filtering versus semantic search, and 'Free, no allowance' signals no quota cost. There is no explicit 'use this when/when not' or named alternative, so the agent must infer the 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 cover read-only/non-destructive/non-idempotent, but the description adds substantial context beyond them: corpus freshness and scale, ranking methodology (measured use rather than votes), a rate limit (free, twenty a day per address or account), and the deliberate absence of a match score with the reason why. For a retrieval tool this is unusually rich disclosure.

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 sentences, front-loaded with the purpose and followed by input format, output semantics, and cost. The middle sentence is long and carries a parenthetical list, but every sentence adds information and nothing is redundant.

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 structure needn't be spelled out, yet the description still supplies the interpretation an agent needs (up to five tools, typed requirement outcomes, no numeric score by design) plus quota and cost. Nothing material is missing for correct invocation.

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 the baseline is 3; the description earns an extra point by reinforcing the free-prose nature of 'need' and enumerating the kind of constraints to embed in it (self-hosted, API, free plan, budget, who will use it). It also clarifies how returned requirement states should be interpreted, which frames what a well-formed input looks like.

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?

Specific verb (find) plus resource (AI tools) qualified by the input form (a described job) and the corpus (the INITE Atlas, ten thousand tools re-read weekly). This is clearly distinguishable from sibling retrieval tools like atlas_search or atlas_lookup, which operate on the dataset rather than matching a natural-language job description.

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 for when this tool applies — you have a described job with constraints and want candidate tools — and tells the caller how much detail to provide ('a sentence or two with any constraint that matters'). It does not name an alternative or state when not to use it (e.g., versus atlas_compare or atlas_lookup), so it stops short of full routing guidance.

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