Datailo: one MCP connection to tenders, EU regulation and law

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

The annotations declare readOnlyHint=true and destructiveHint=false, yet the description states 'action='revoke_key' ... revokes one,' which is a state-changing operation. This is a direct annotation contradiction, and the description cannot be trusted as written.

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 dense sentences with no filler. The purpose is front-loaded, and the security-relevant note 'never the key' earns its 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?

Despite the action examples, the description omits output expectations, the irreversibility of key revocation, and any auth/session context beyond the schema. The annotation contradiction makes the behavioral context incomplete and potentially misleading for an agent.

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%, but the description compensates for the bare 'action' and 'key_prefix' parameters by showing exact usage ('action='keys'', 'revoke_key' with key_prefix). The 'session' parameter is already thoroughly described in the schema.

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 (the connected account) and gives concrete actions: 'keys' lists dat_ keys and 'revoke_key' revokes one. It clearly conveys what the tool does, though it does not explicitly compare itself with sibling tools.

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 explains two action values but gives no guidance on when to prefer this tool over siblings such as datailo_connect or datailo_plan. No exclusions, prerequisites, or alternative routing are provided.

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/idempotent/non-destructive/open-world, yet the description adds real value beyond them: the required auth sequence, the exact set of returned fields, provenance ('rendered from each service's live product card, never hand-written'), and an edge case (card: 'unavailable' when no card exists). No pagination or rate-limit behavior is disclosed, keeping it short of 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 blocking auth requirement before the payload description, and every sentence carries information (auth, content, provenance, fallback). Dense but not padded, though the auth clause is long enough to slightly blunt the opening.

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 browse tool with no output schema, the description usefully describes the return shape, data origin, and a fallback case, and the annotations cover safety. The main gap is the two unexplained parameters (q, audience), which no structured field clarifies.

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 33%: only 'session' is documented in the schema, and the description adds nothing about any parameter. Critically, 'q' (presumably a search/filter) and 'audience' are undocumented in both places, so the description fails to compensate 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?

Clear verb+resource: it returns 'compact rows for every federated service' and enumerates the fields (name, job, datasets, tool/workflow counts, tiers, enabled status). The scope word 'every federated service' implicitly separates it from single-service siblings like datailo_describe, but no sibling is named explicitly.

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 strong prerequisite guidance — sign in via datailo_connect and datailo_connect_verify first — plus the exception when already authenticated. However, it never states when to choose this over datailo_describe, datailo_tools, or datailo_start_here, 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 only include readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false, so the description carries the burden. It discloses that an email is sent with a confirm link and six-digit code, that a request_id is returned, that the account is created on first confirmation, and that nothing is charged. This is transparent, though it does not mention failure modes or what happens if the email is not confirmed.

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 concise enough and front-loaded with the purpose. It is structured logically: purpose, parameters, behavior, next step. Each sentence adds value, though the instruction to tell the user and then call verify could be slightly more compact, it is clear and not overly verbose.

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-step authentication tool with two parameters and no output schema, the description covers the essential information: purpose, parameters, the email behavior, the return of request_id, the need to call verify, and the no-charge/no-card aspect. It lacks details on error handling or the exact structure of request_id, but that is not critical for 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 0%, so the description must explain parameters. It mentions 'email' and 'language' and explains the language is the language spoken with the user, with examples ('lt', 'en', 'de'). It clarifies that language is optional via the default, and that email is sent in that language. This adds meaning beyond the schema's bare property definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Sign in, inside the chat (needed to enable services and call their tools).' It explicitly identifies it as step 1 of 2 and differentiates it from the sibling datailo_connect_verify by describing the subsequent call. The verb 'sign in' and the resource 'Datailo' are specific, and the scope is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: 'needed to enable services and call their tools.' It also instructs the agent to tell the user to click the confirm link and then immediately call datailo_connect_verify(request_id), which defines the flow. It does not explicitly state alternatives (since there are none for sign-in), but the guidance is sufficient.

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 are sparse (no safety hints), so the description carries the burden and does so thoroughly. It discloses that the tool waits up to 45 s, returns a waiting status, requires repeated calls, issues a durable dat_ key (shown once), and provides a session value when needed. No contradictions with annotations; this is exemplary behavioral 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?

The description is a single dense paragraph with no filler. It front-loads the purpose, then gives step-by-step instructions and edge cases. Every sentence earns its place, using emphasis (RIGHT AFTER) for critical timing. It is efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and only two parameters, the description covers when to call, how to call, what to expect (waiting/success), retry logic, and post-success actions. It even addresses the client session edge case. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description explains both parameters: request_id is required (from step 1) and code is optional (if user reads it). It clarifies the semantics of 'no code' vs 'pass it as code'. This compensates fully 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 the exact purpose: 'Finish signing in' and identifies it as step 2 of 2, clearly distinguishing it from the sibling datailo_connect (step 1). It specifies the action (verify sign-in) and the resource (connection session). An agent can immediately understand what this tool does and how it differs from its 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?

Explicit guidance: 'Call it RIGHT AFTER datailo_connect' with specific instructions on passing request_id and optionally code. It tells when to call again (if returns waiting) and what not to do ('do not ask the user to report the click'). It also explains post-success steps (carry on with user's request). This fully equips the agent to use the tool correctly.

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, openWorld behavior, so the safety profile is covered. The description adds genuinely new behavioral context the annotations cannot express: a mandatory auth handshake and its cost. It does not describe rate limits, errors, or return shape beyond the field list.

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 dense sentences with no filler; every clause earns its place. Leading with the auth prerequisite is defensible since it is blocking, though it delays the statement of purpose slightly.

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 usefully enumerates the returned card contents, and it covers the auth prerequisite. The main gap is that an agent cannot tell how to construct the required 'service' value, which matters for a one-required-param tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% for the single required 'service' parameter, so the description carries the full burden. It only says 'one service', restating the parameter name, and never states the expected format (slug, name, or ID from datailo_catalog) or where 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 names a specific verb+resource ('The full product card for one service') and enumerates the returned content (tagline, datasets, workflows, tiers, docs), so an agent knows exactly what this produces. It does not explicitly contrast itself with the listing sibling datailo_catalog, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit, actionable precondition: sign in via datailo_connect(email) and datailo_connect_verify first unless already signed in, including that this is free and costs one email. It stops short of saying when to prefer this over datailo_catalog or how to obtain a valid service identifier.

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

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

Annotations already declare destructiveHint=true, idempotentHint=true and openWorldHint=true, but the description adds real value beyond them: it explains exactly what is destroyed (the hub's key) and reassures that the account and its data remain the user's, scoping the blast radius. It does not say whether disabling is reversible or what a repeat call returns.

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 sign-in prerequisite before the action itself. The auth preamble is slightly long relative to the core statement, but each sentence carries necessary 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?

For a destructive two-parameter tool with no output schema, the description covers auth and destruction scope well, but leaves the service identifier undocumented and does not mention reversibility via datailo_enable or behavior on repeated calls. The absence of an output schema removes any need to describe return values.

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%: the session parameter is fully documented in the schema, but 'service' has no description anywhere. The description says 'a service' without indicating the expected identifier format (name, slug, ID) or accepted values, so it does not compensate for the coverage gap. Baseline 3 for the half-covered schema.

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 ('Disable a service: revokes the hub's key for it') and clarifies the scope of the effect. It is clearly the inverse of the sibling datailo_enable, though it never names that sibling to sharpen 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?

It gives explicit prerequisites (call datailo_connect(email) and datailo_connect_verify first, or omit if the connection is already signed in via OAuth/key), which is strong usage context. It stops short of stating when NOT to disable or pointing to datailo_enable as the reversal path.

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

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

Annotations only declare the general safety profile (non-readOnly, openWorld, idempotent, non-destructive). The description adds substantive side-effect detail the annotations cannot: sign-in is required, the hub links or creates an account on the target service using your email, it stores an encrypted key, and keyless services are enabled as a trial (a billing implication). This is exactly the kind of behavioral context annotations don't 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?

Front-loads the critical prerequisite (sign-in required) before describing the action, and each sentence carries distinct information. Slightly dense but no filler; four sentences all 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?

For a mutating, open-world tool with no output schema, the description covers the workflow, side effects, and auth prerequisites well. However, the undefined `plan` and `service` parameters leave a real gap, and the return/result of enabling is unaddressed.

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% – just `session` is documented in the schema, and the description merely restates its sign-in context without adding more. The `service` and `plan` parameters are undocumented in both schema and description; `plan` in particular is unexplained, so the description fails to compensate for the low coverage as it should.

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: 'Enable a federated service on your Datailo account,' and explains the downstream effect (datailo_tools and datailo_invoke reach it through this connection). It is clearly distinguishable from the opposite action datailo_disable, though it never names that sibling explicitly for contrast.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit prerequisite chain: call datailo_connect(email) and datailo_connect_verify first unless already signed in, and notes the session requirement for subsequent calls. It doesn't state when to use an alternative (e.g., datailo_disable) or any exclusion cases, 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.

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

Annotations only declare readOnlyHint=false and openWorldHint=true; the description usefully adds the authentication requirement and the fact that the service's own result is returned unchanged. It does not warn that a child tool may be destructive or that failures surface as the child's errors, so it is strong but not fully exhaustive.

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. The blocking prerequisite (sign-in) is front-loaded before the functional description, which is the correct priority order for an agent that must clear auth before calling.

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?

No output schema exists, and the description covers the gap minimally with 'Returns the service's own result'; auth and sibling discovery are covered. Error behavior and how to discover which services are enabled are left implicit, but nothing essential for a correct call is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25% (only `session` is documented), so the description has to carry the load. It identifies service, tool name and arguments, and points to datailo_tool_schema for the passthrough `args` shape, but adds no format, naming convention, or validation detail beyond restating the 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?

States a specific verb and resource: it calls exactly one tool of an enabled service through the hub, taking service, tool name and arguments. It also names the sibling that explains the argument shape (datailo_tool_schema), so the agent can distinguish it from connection and catalog tools without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives the prerequisite flow explicitly (call datailo_connect(email) then datailo_connect_verify first), states the exception (unless already signed in), and routes the agent to datailo_tool_schema for the child tool's argument contract. The when-to-use condition and the alternative are both spelled out.

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 mark this as non-read-only, non-destructive and non-idempotent, and the description adds context annotations cannot: the required sign-in sequence and the fact that the beta is free with no charge and no checkout link returned. It stops short of explaining what 'discontinue' actually does (reversible? immediate?), which for a state-changing action would be valuable.

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, no filler, with the auth prerequisite front-loaded ahead of the functional description. The cramming of four action values into a parenthetical keeps it dense but readable.

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 usefully notes what is not returned (no checkout link), and auth is covered. But for a tool whose actions create, modify and terminate a plan, the absence of any detail on side effects, required permissions per action, or the role of 'tier' leaves meaningful gaps.

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 carries real weight here: it supplies the allowed values for 'action', which the schema leaves as an unconstrained string with no enum or description. However, 'tier' (needed for 'change') and 'service' are never explained, so the description only partially 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?

The description names a specific resource (a service's plan) and enumerates the concrete actions it supports (status | enroll | change | discontinue), which is far more specific than the title 'Manage a plan'. The opening verb 'See' is a slight mismatch with the mutating actions 'enroll/change/discontinue', but the action list resolves the ambiguity. It is clearly distinguishable from siblings like datailo_catalog or datailo_describe.

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 an explicit prerequisite flow, naming datailo_connect and datailo_connect_verify by tool name and noting the OAuth/key exception. It also scopes usage to plan management via the action list. It does not, however, say when to prefer this over other Datailo tools or what happens if a service has no plan.

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), so the bar is lower; the description still adds real context by disclosing the sign-in prerequisite, that the flow is free/one email, and what the response contains. It stops short of describing response shape in detail, but no output schema exists and the orientation contents are enumerated.

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 the blocking sign-in requirement before the orientation purpose, so the agent reads the prerequisite first. Every sentence earns its place, though the second sentence packs several output categories into one clause.

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 carries the burden of explaining return content and does so (cross-service jobs listed first, enabled services, available services, next steps). The auth prerequisite and call ordering are both covered, leaving nothing an agent needs in order to invoke 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 session parameter is fully documented in the schema, so the schema does the heavy lifting. The description references the sign-in flow the session relates to but adds no syntax or format detail beyond what the schema provides — baseline 3.

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 purpose — orientation for a new connection that surfaces cross-service jobs, enabled/available services, and next steps — plus the entry-point role via 'Call this first.' An agent can tell this apart from datailo_account or datailo_tools because it is explicitly framed as the starting orientation call.

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 explicit when-to-use guidance ('Call this first') and states the prerequisite sign-in path, naming the exact sibling calls (datailo_connect, datailo_connect_verify) plus the exception for OAuth/key connections. Nothing about when to invoke it 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 already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds genuinely new behaviour: results are read live from each service, ranking prioritises name and title matches, and the list is capped at a default of 50. It does not describe pagination or failure modes.

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 dense paragraph with the blocking prerequisite front-loaded before the search behaviour, so an agent hits the critical gate first. It is slightly run-on but every clause carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only search tool with no output schema, the description covers the auth gate, the source of results, ranking logic and the default limit. Return-value shape is the only notable omission, and the ranking/limit notes partly compensate.

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 20% (session alone is documented), so the description has to carry the rest and does: q accepts words or a whole sentence and drives word-based ranking, service narrows to one service, include_available previews enableable services, and limit defaults to 50. Only the session parameter is left to the schema, and no accepted values or format for service are given.

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: 'Search the tools of your enabled services (read live from each service)'. It is clearly distinguishable from write-oriented siblings like datailo_enable or datailo_invoke, though it does not explicitly contrast itself with near-neighbours such as datailo_describe or datailo_tool_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?

It gives an explicit precondition and the alternative path for it: 'call datailo_connect(email) and datailo_connect_verify first ... unless this connection is already signed in'. It also explains the purpose of the service and include_available switches. It stops short of saying when to prefer this search over datailo_catalog or datailo_describe.

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), so the description's added value is the auth flow and a hint at the return content ('full input schema ... and how to call it'). It adds real context beyond the structured fields and contradicts nothing, but says nothing about returned schema size or limits.

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 the blocking prerequisite front-loaded, which is the most important thing for an agent to read first. The auth instruction is long but load-bearing; minimal waste.

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, and the description does at least signal what is returned (the input schema plus call instructions) and how to authenticate. It omits how to discover valid service/tool identifiers and any caveats about the returned schema, leaving gaps for a lookup-style tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33%: 'session' is documented in the schema itself, but 'tool' and 'service' are bare strings. The description partially compensates by implying the service must be enabled and the tool belongs to it, yet it never says where to obtain valid names or whether they must match datailo_tools output.

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 resource: 'the full input schema for one tool of an enabled service, and how to call it.' An agent can distinguish it from the listing siblings (datailo_tools, datailo_catalog) by its schema-retrieval role, though no sibling is named explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit conditional prerequisite: sign in via datailo_connect(email) and datailo_connect_verify 'unless this connection is already signed in.' That is clear when-to-use guidance. It does not, however, say when to prefer this over datailo_tools, datailo_describe, or datailo_invoke.

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 read-only, idempotent, non-destructive, open-world behavior, and the description adds genuinely useful context beyond that: the sign-in prerequisite, the need to pass the session on every subsequent Datailo call, and what the response contains (services to enable, stages, checkpoints, work-product template). It stops short of describing error behavior when the service/name pair is unknown.

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 dense sentences with no filler; the auth prerequisite is correctly front-loaded. The second sentence packs both the per-step annotation behavior and the job-name variant into one clause, which reads slightly run-on but still earns its length.

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 must describe returns, and it does outline the job contents (services, stages, playbooks, checkpoints, template). However, it omits the shape of the returned steps, pagination/size behavior, and valid 'service' values, so an agent can call it but cannot fully anticipate the response.

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 session is documented in the schema – so the description must compensate. It does explain one service value ('datailo' with a job name yields the whole job) and reinforces session-passing, but it leaves the required 'name' parameter and the remaining service values undefined. 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?

The second sentence states the resource and its scope: it returns one playbook's steps, each annotated with the datailo_invoke call to run it, and notes the service='datailo'+job-name variant that returns the full job. It never names the plural sibling datailo_workflows, so the singular/plural distinction is left implicit, and the purpose is buried behind the auth preamble.

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 an explicit precondition (call datailo_connect and datailo_connect_verify first, unless already signed in) and routes the agent to datailo_invoke for executing the returned steps. It does not say when to prefer this over datailo_workflows, datailo_plan, or datailo_catalog, so sibling selection is only partly resolved.

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, openWorld and non-destructive, so the safety profile is covered. The description adds meaningful non-schema behavior: the required sign-in/connect handshake and the result ordering (cross-service jobs first, then playbooks flagged enabled/not). It does not mention pagination or result size limits.

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 with the prerequisite front-loaded and no filler. It reads as slightly run-on, but every clause carries information (auth, ordering, how to open a result).

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 list tool with no output schema, the description covers auth requirements, return ordering, and the enabled/disabled flag, which is most of what an agent needs to call it and interpret results. The undocumented `q` and `service` semantics are the remaining 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 only 33%: only `session` is documented in the schema. The description touches the 'service' concept (service 'datailo', kind 'job') but never explains how the `service` filter or the `q` query parameter actually behave, so it does not compensate for the coverage gap on two of three 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 makes clear the tool lists workflows — cross-service jobs first, then per-service playbooks — and explicitly distinguishes itself from datailo_workflow, which is used to open one. The verb is only implied (carried mostly by the title) but the resource and ordering are precise enough for an agent to know what it returns.

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 authentication prerequisite (call datailo_connect and datailo_connect_verify first) and routes the agent to datailo_workflow for opening a result. It lacks an explicit 'use this when you want to discover/list workflows' framing, but the context and the named alternative give usable 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?

Adds substantial context beyond annotations: authentication requirement, that action='reply' with confirmed=true puts the item back on the team's desk, visibility scope (account sees own items; a Datailo reviewer sees all), and an explicit prompt-injection warning that quoted thread text is data and must not be followed.

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 auth requirement, then action semantics, then the security caveat, so scanning order matches decision order. It is a dense single block, but nearly every sentence carries operational information rather than 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?

With no output schema, the description carries the return-shape burden and does: action='get' returns the item (sent content, status, ticket, release, timeline) plus the thread; action='list' returns status and whether the team answered, with no message texts. An agent has what it needs to call and interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (baseline 3), but the description still adds value: the DAT-FB-<number> ref format, the semantic meaning of full (latest whole, older shortened), when to pass session vs omit it for OAuth/key, and that confirmed requires the person to have agreed the text.

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 specific verbs and resource: read one feedback item and its whole thread, or answer in it, plus a list mode. An agent can distinguish this from submit_feedback (create) and notifications 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?

Explicit routing: fetch with action='get' before answering, and clear preconditions (sign in via datailo_connect/datailo_connect_verify first, or pass session). It does not explicitly contrast itself with the submit_feedback sibling for creating new items, so it stops short of naming 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 only say mutating/non-idempotent/open-world; the description adds the real behavioral context: read marks a message read, reply goes into the feedback thread and requires confirmed=true only after the person approves the exact words, dismiss/snooze put messages away, and unauthenticated use shows only service notices. It also discloses that the tool is untrusted-data-oriented with explicit safety rules, 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?

The prose is dense and nearly every sentence carries information: auth, action semantics, surfacing rule, safety policy, anonymous-mode fallback, sibling routing. It is long but not padded. Slight deduction because the auth preamble and safety policy are interleaved rather than sectioned, making the purpose statement less 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?

For a 7-parameter multi-action mutating tool with no output schema, the description covers auth, per-action effects, confirmation gating, anonymous behavior and safety. It does not describe the shape of what 'list' returns (unread counts, message fields) or pagination, which an agent would otherwise have to discover.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents id, body, hours, action, settings and confirmed, including per-action pairings. The description mirrors this ('read with id', 'snooze (hours)', 'reply with id and body') rather than adding new syntax or constraints, so it sits at the baseline 3.

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 (messages from the Datailo team to this person) and enumerates concrete verbs for each action (list, read, reply, dismiss, snooze, settings), including what each does. It is clearly distinct from siblings like feedback/submit_feedback because it explicitly frames these as team replies to the person's feedback. It stops short of a one-line contrast against those siblings, hence 4 rather than 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Auth prerequisites are stated up front (datailo_connect/datailo_connect_verify, or already signed in), each action's condition of use is given, and the agent is told exactly when to surface messages ('when an answer carries a notifications block with unread messages... their task comes first'). It even routes to the sibling path for per-service unread messages.

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 say this is a non-read-only, non-idempotent, open-world write. The description adds materially more: sign-in prerequisite via datailo_connect/verify, the requirement to show the user content before sending, the confirmed=true gate, the authored_by='agent' exception for the agent's own observations, per-field and 80,000-character total limits, and what the caller may/may not promise about a reply.

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?

Five dense paragraphs is long, but nearly every sentence carries an actionable rule (gating, consent, length caps, routing, reply expectations) rather than filler. The sign-in prerequisite is front-loaded, though it precedes the statement of purpose, which delays the 'what does this do' answer slightly.

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 13-parameter write tool with no output schema, the description covers the prerequisites, the consent workflow, per-field sizing, service routing, and the fact that the response carries a reference id. An agent has enough to invoke it correctly without guessing at policy.

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 baseline is 3, but the description adds real meaning on top: when to set expected/got (only for a wrong answer), that contact_email is only for a requested reply, how service routes feedback to 'avokata'/'victano'/'rekvira', and the combined item-size budget. It omits the `message` legacy alias and the `session` parameter, which the schema covers anyway.

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 with scope: 'Send feedback about Datailo to the team that builds it', and enumerates the kinds of items (bug, wrong answer, missing data, feature, workflow idea, praise). It does not differentiate itself from the sibling tool named `feedback`, which an agent could plausibly confuse with this one.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit 'When to offer it' list of triggering situations (empty or wrong answer, user correction, missing workflow step, repeated manual step, unmet need) plus a hard constraint: offer once, in one sentence, user's task first. The ask-first/confirm flow is spelled out as a precondition rather than left to inference.

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