ScopeLinq

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds useful behavioral context beyond annotations, including that it works for both senders and receivers, requires no account, and that its output cites one of the confirmed lines. This goes beyond the structured annotation data.

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

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

The description is front-loaded with the core purpose and then delivers compact, useful operational constraints and prerequisites. Every sentence carries information an agent needs: what it answers, how to cite lines, what to avoid passing, when to use the sibling tool, applicability, and cost/authentication status. No wasted words.

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 only two parameters, full schema coverage, and an output schema, the description is complete. It covers the decision categories, input requirements, exclusions, prerequisite workflow, and scope of who can use it. Nothing an agent needs to invoke this tool correctly appears to be 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 100%, so the baseline is 3, but the description adds meaningful semantic constraints: only pass lines the person confirmed, never pass lines from not_found_in_text unless confirmed, and never pass the original document. These are important nuances not fully expressed in the schema and help the agent populate confirmed_lines correctly.

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 exactly what the tool does: it classifies a new request as Included, Additional work, or Needs clarification and cites a confirmed line. It also clearly distinguishes its role from the sibling tool by indicating when draft_scope_record should be used instead, so an agent can tell them apart.

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

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

The description gives explicit when-to-use guidance: if no lines have been confirmed, call draft_scope_record first and ask the person. It also provides clear exclusions, such as never passing lines from not_found_in_text unless confirmed and never passing the original document, which prevents incorrect usage.

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?

Discloses two important behavioral facts beyond annotations: the text is processed by an AI model and is deleted within 24 hours. It also instructs the user to remove PII, clarifying data-handling expectations. This meaningfully extends the read-only perspective already marked by 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?

Every sentence earns its place: purpose, recipient orientation, exact-text handling, redaction, output shape, next step, data deletion, and account requirement. It is dense but not verbose, with no repetition of the schema and 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 single-parameter, read-only tool, the description covers all necessary operational details: input format, PII handling, output semantics, follow-up action, privacy, and cost. The output schema likely encodes structures, but the description explains the meaning and step-by-step usage, leaving no guesswork.

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 schema already documents the agreement_text parameter well, so the baseline is 3. The description adds useful operational guidance: pass the text exactly as written, do not summarise first, and remove names, emails, and account numbers before pasting. This goes beyond a mechanical schema-required description and makes invocation safer.

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, and outcome: it reads a document (proposal, quote, contract, etc.) and returns the terms it actually states, each traced to the words it came from. It also differentiates from the sibling check_scope_change by explaining how to use that tool after.

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 a clear workflow: pass the exact text, show the returned lists to the user, ask which lines were agreed, then call check_scope_change with only those. It tells the agent when to use this tool and how to proceed, though it does not spell out explicit negative use cases.

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