Questa Privacy MCP

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

Annotations already declare readOnly=false, destructive=false, idempotent=false and openWorld=true, so safety is partly covered. The description adds genuinely new behavior: Excel jobs are long-running, jobs return a job_id to poll, and re-uploading is discouraged. Payload handling ('never paste file bytes in chat') and the default regime are useful operational details 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-loads the core capability, then flows into workflow and caveats in a compact block. The sentence 'Parameters include upload_id...' is somewhat redundant with the schema but is short enough not to bloat the definition.

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 multi-input async tool with no output schema, the description supplies the critical missing pieces: which input mode to use (upload vs inline text vs path), the async polling behavior, and the job_id return. Only the return payload shape (e.g. status fields) is left implicit, which keeps it short of a 5.

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 88%, so parameters are already well documented in the schema. The description enumerates the parameter names and clarifies the upload_id workflow, but this largely restates what the schema's per-parameter descriptions already say, 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 specific verb (anonymize) plus the resources it accepts (text or pdf/docx/csv/xlsx files) and the compliance regimes it supports, so the agent knows exactly what the tool produces. It does not, however, distinguish itself from the sibling redact_pii, which an agent could plausibly confuse with anonymization.

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 a concrete workflow ('After chunk upload, call this with upload_id + filename + regime') and names an alternative with its triggering condition ('if status is running, call get_anonymize_job ... do not re-upload'), which is strong when-to-use guidance. It stops short of explaining when to prefer this over the redact_pii 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 already declare readOnly/idempotent/non-destructive/openWorld, so the safety profile is covered. The description adds genuinely useful behavior beyond that: this is a polling endpoint whose useful payload (the preview) only appears once the job is completed, and re-uploading is not the recovery path.

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 compact sentences, front-loaded with the action and result. One sentence is marred by the truncated 'job cmup… IDs' text, which reads as a defect rather than intentional brevity.

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 an async job-polling tool with no output schema, the description covers the important things: when to call it, that results arrive only on completion, and the re-upload pitfall. It stops short of stating terminal failure states or polling cadence, which would make it fully self-sufficient.

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?

Only one parameter and the schema documents it at 100% ('Job id from anonymize_document'). The description reinforces the source of the id but adds no format or syntax detail beyond what the schema already says, 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 specific verb+resource ('Check an anonymize job') and adds the key output behavior ('return the preview when it is completed'), which distinguishes it from anonymize_document. The stray truncated fragment 'job cmup… IDs' slightly blurs an otherwise clear statement.

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 explicit trigger conditions: use after anonymize_document returns running/queued, or to recover job IDs, plus a clear prohibition ('Do not re-upload the file'). It names the sibling and the state that selects this tool, though the truncated 'recover job cmup… IDs' clause is partially unusable.

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=true, idempotentHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is fully covered. The description adds genuinely new behavioral context by disclosing that results are filtered by 'the current SaaS role,' which is not encoded in any annotation. It does not describe the shape of the returned list, but that is minor for a zero-argument 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?

A single sentence with the verb and the role-scoping constraint front-loaded, and no filler. Every word 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?

For a no-argument, read-only, annotation-rich listing tool this is close to sufficient: what is listed and under what scope are both stated. The only omission is the return shape (names only vs. names with descriptions/metadata), which an agent might want since 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?

The tool takes zero parameters and the input schema is an empty object, so there is nothing for the description to disambiguate. Baseline of 4 applies; the description neither adds nor omits parameter 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?

Specific verb ('List') plus two concrete resources ('/questa:* commands and MCP tools') scoped by role. The four sibling tools (anonymize_document, redact_pii, review_with_claude_legal) are clearly unrelated, so an agent can place this tool without ambiguity, though the description does not explicitly distinguish itself from any of them.

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 implicit: an agent can infer it should call this to discover what the current role is permitted to run, but there is no explicit when-to-use, when-not-to-use, or prerequisite (e.g. that a SaaS role must already be established). No alternatives exist among the siblings, so the absence is less damaging than it would otherwise be.

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, so the safety profile is covered. The description adds real value beyond them: it states the return content (redacted text plus preview), the external-boundary guarantee (no send to Claude Legal), and an auth prerequisite ('Requires tools.text'). It does not explain irreversibility or whether the source is modified.

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, zero padding, and the core capability is front-loaded before the boundary and workflow conditions. Every sentence carries distinct 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?

Return values are adequately covered despite no output schema, and the auth/workflow context is present. The main gap is the undocumented entity_types vocabulary, which an agent needs in order to call the tool correctly for a 0%-coverage 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 0% for two required parameters. The phrase 'by entity type' hints that entity_types controls which entities are redacted, but no valid entity values or format are given, and the text parameter's accepted input is never addressed. The description only partially compensates for a total schema documentation 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 verb (redaction) and resource (personal data in contracts, emails, transcripts) with scope qualifier 'by entity type.' It is clear what the tool does, though it never names the closest sibling anonymize_document, so sibling differentiation is only implicit.

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 concrete workflow routing: 'Does not send content to Claude Legal' and 'If Claude Legal is enabled, wait for the user to confirm then call review_with_claude_legal.' That is explicit sequencing against a named sibling. It stops short of saying when to prefer this over anonymize_document.

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, destructiveHint=false, idempotentHint=false, openWorldHint=true). The description adds genuinely non-structured behavior: an explicit user-confirmation gate before invoking an external service. It does not mention cost, latency, or failure behavior, keeping it below a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, no padding, with the action and the precondition front-loaded and the parameter requirement last. Every sentence carries required 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?

There is no output schema, but the description does not need to describe return values since it covers the call preconditions and input contract fully. Minor gap: nothing about what happens on rejection or how results are surfaced.

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 adds meaning beyond the schema by specifying the either/or requirement between job_id and map_id and flagging anonymized_text as the fallback path, which the flat schema does not express.

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: send anonymized text or a completed file job to Claude Legal. The 'already-anonymized' and 'completed file job' qualifiers implicitly separate it from anonymize_document and redact_pii, though no sibling is named directly.

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 a clear precondition chain: call only after the user has previewed the anonymized content and confirmed. It also states the required inputs (confirmed=true plus job_id or map_id). No explicit exclusion or named alternative, but the sequencing relative to the anonymize step is unambiguous.

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 this is a non-read-only, non-destructive, non-idempotent write, so the safety bar is partly met structurally. The description adds chunk-size and sequencing behavior, but says nothing about persistence, retention of uploaded chunks, or auth needs, and the phantom 'complete=true' flag conflicts with the actual schema.

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 purpose and immediately followed by the size guidance and the workflow ordering. Every sentence carries information, with only a minor deduction for the misleading 'complete=true' token.

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 multi-step chunked upload with no output schema, the description supplies the chunk strategy, size range, and the required follow-up call, which is most of what an agent needs. It omits error handling and what upload_id looks like on return, but is otherwise solid.

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, but the description adds genuinely non-schema semantics: the 4000–8000 character guidance for chunk_base64 and the note that upload_id is used to chain into anonymize_document. That is real meaning beyond what the schema documents.

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 (send) and resource (a Claude/Cowork file as base64 chunks) and clearly differentiates itself from siblings by naming the anonymize_document follow-up. The odd reference to 'complete=true' — a parameter that does not exist in the schema — slightly muddies the mechanism.

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?

Provides concrete operational guidance ('prefer 4000–8000 characters per chunk'), specifies the sequencing ('After complete=true, call anonymize_document with...'), and adds a prohibition ('Do not extract spreadsheet or document text'). This gives the agent both the next step and a boundary, though it doesn't cover failure/retry conditions.

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