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

With no annotations provided, the description carries the full behavioral burden. It discloses that verification happens offline against a built-in public key, that the key is persisted to the config file, and that invalid keys are refused and left unsaved. This is substantial transparency for an activation tool, though it could mention overwriting an existing key or the exact return behavior.

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 two sentences with no filler. The first sentence front-loads the main action, source, verification method, and persistence. The second sentence efficiently covers error handling and points to the related read-back tool. Every clause adds value.

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

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

Given a single-parameter tool with no output schema and no annotations, the description covers activation behavior, verification mechanism, persistence, error outcomes, and how to read the result later. The only minor gap is an explicit statement of what the function returns upon success or failure, but the phrase 'refused, unsaved' implies a feedback mechanism. Overall, it is sufficiently complete for an agent to call 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?

The schema already documents the 'key' parameter at 100% coverage, so the baseline is 3. The description adds meaningful semantics by giving the concrete key format ('MCPL1.xxx.yyy'), confirming the key comes from the checkout page, and explaining that malformed or expired keys will be rejected. This goes beyond the schema's one-line description.

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 action ('Activate a Pro key'), the exact key format ('MCPL1.xxx.yyy'), the source ('from checkout'), and the core mechanism ('verified offline against a built-in public key'). It also differentiates itself from the sibling license_status by noting that license_status reads the activation back, so there is no ambiguity about which tool does what.

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 clear context: use this when you have a Pro key from checkout that needs to be activated. It also points to license_status as the read-back tool, which implies when to use a related sibling. It does not explicitly spell out 'do not use for checking status' or list other alternatives, but the context is strong enough to avoid misuse.

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 absent, so the description carries the full burden of behavioral disclosure. It discloses that the call is local ('no network') and argument-free, and it mentions a specific explanatory behavior. The word 'Report' implies read-only, though it does not explicitly state non-destructive or permission requirements; this is adequate for a status command.

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 first sentence lists the output fields; the second adds constraints and the sibling pointer. Every clause contributes meaningful 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 zero-parameter status tool with no output schema, the description lists the expected output fields, behavioral constraints, and the relevant alternative tool. 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?

The schema has zero parameters and the description reinforces this with 'No arguments'. It adds value by listing the reported fields, helping an agent understand what the empty input will yield. The baseline for zero-parameter tools is high, and the description meets 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 specific verb ('Report'), a clear resource ('this server's licence state'), and enumerates the exact fields returned. It also names the sibling 'license_activate' as the tool that does something different, so an agent can distinguish them immediately.

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

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

The description gives explicit usage constraints: no arguments, no network, and explains a free-tier refusal. It also directs the agent to license_activate when the task is to install a key, serving as an explicit pointer to the relevant alternative.

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

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

The description adds valuable behavioral context beyond the annotations by explaining that the source file is never modified unless out_path points at it, and by summarizing the return value. It also clarifies the tool creates a new file, which is important given readOnlyHint is false and destructiveHint is false.

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 two sentences with no fluff: it front-loads the tool's purpose and key safety behavior, then lists the return values. Every sentence 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?

The description is complete for selecting and invoking this tool, especially paired with a fully documented schema. It explains what the tool does, where results go, what safety guarantee applies, and what the caller receives in return.

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 all parameter meanings. The description does not add per-parameter semantics beyond the schema, so the baseline score of 3 is 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 states a specific verb and resource: add a computed column and save the result to a new file. It also distinguishes the tool's core behavior from siblings by emphasizing that the source remains untouched unless out_path points at it.

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 clear context for when to call this tool: to add a computed column and produce a new file. It does not explicitly name alternatives or exclusion conditions, but the intended use is unmistakable from the first sentence.

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 convey readOnlyHint=false and destructiveHint=false, establishing this as a non-destructive write. The description adds valuable context beyond those flags: it writes a new file next to the source by default, guarantees 'the source is never modified', and discloses the return payload (new file path with row and column counts). This is consistent with the annotations and enriches them with concrete behavior an agent needs.

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 with no waste: purpose first, then side-effect behavior, then return value. Each sentence carries distinct information (what it does, where output goes, what comes back), and the canonical 'Call this tool to...' opener front-loads the decision-relevant purpose.

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 correctly compensates by explaining the return value (new file path plus row and column counts). Combined with 100% schema parameter coverage and consistent annotations, an agent has what it needs to invoke correctly. The only minor gap is the unstated relationship to the sheet_load/sheet_unload workflow — it does not say whether the source file must be loaded in the workspace first.

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 all four parameters (path, to, sheet, out_path) are already well-documented in the schema. The description adds no parameter-level semantics beyond what the schema states — the 'source is never modified' claim and out_path default behavior are both already present in the schema's parameter descriptions. 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 opening sentence states a specific verb and resource — 'convert a sheet between excel (xlsx), csv and json' — which clearly differentiates this tool from siblings like sheet_read, sheet_write, sheet_load, and sheet_add_column. An agent can immediately tell this is a format-conversion tool, not a read/write/query 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?

'Call this tool to convert a sheet between excel (xlsx), csv and json' provides an explicit trigger condition for when to invoke it. However, it does not name alternatives or state when NOT to use it (e.g., no mention that in-place editing should use sheet_write). The context is clear but lacks explicit exclusions.

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

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

The description adds useful behavioral details beyond the annotations: matching is case insensitive, and it returns cell addresses with a row preview. Since annotations provide no positive safety signal and the tool is a search operation, this is reasonably transparent, though it could have explicitly stated it does not modify the file.

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 two sentences and front-loads the core purpose with 'Call this tool to search every cell...' followed by a brief rationale and key behavioral details. Every sentence adds value and there is no redundancy.

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 simple search tool with full schema coverage, the description adequately explains return shape (cell addresses with row preview) and matching behavior. It is slightly incomplete in that it does not describe error conditions or explicitly confirm no side effects, but these are minor for this operation.

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 input schema fully documents all three parameters. The description adds high-level behavior but does not materially extend parameter-level meaning beyond what the schema already provides, meriting the baseline score.

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 action: 'search every cell of a spreadsheet or CSV for text.' This clearly distinguishes the tool from siblings like sheet_read and sheet_query, which read or query structured data rather than doing a raw cell-by-cell text search.

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 clear context for when to use the tool: when searching spreadsheets for text, noting that 'built-in file readers cannot parse spreadsheets.' It does not explicitly name alternative sibling tools or state when not to use it, so it misses the top tier of explicit exclusions.

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 all annotations false, the description carries the full burden and does list the return content (sheet names, size, header row, column types, samples). However, it says nothing about whether the tool modifies anything, requires special permissions, or how it handles invalid paths, so behavioral disclosure is only partial.

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 short sentences with no filler. The routing instruction and the prohibition on built-in readers come first, followed by a compact list of the output's contents, making it easy for an agent to scan.

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 simple one-parameter info tool with no output schema, the description adequately states what the agent will get. It could be more complete by noting that the tool is read-only or what happens on missing/invalid files, but those are minor gaps given the tool's simplicity.

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 single path parameter is 100% covered by the input schema, including accepted extensions and tilde expansion. The description only restates 'any spreadsheet or CSV file path', adding no syntax, formatting, or usage details beyond the schema, so the baseline 3 is 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 clearly defines the tool as a spreadsheet/CSV overview entry point, stating exactly what it returns: sheet names, size, header row, column types, and samples. It distinguishes itself from built-in file readers, but does not explicitly route between sibling sheet_* tools, so it falls just 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 explicitly says to call this tool for any spreadsheet or CSV file path and forbids using built-in readers for them, which is a strong when-to-use/when-not-to-use rule. It also positions the tool as 'start here', but it does not give explicit conditions for preferring siblings like sheet_read or sheet_stats over 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?

Annotations are present but sparse, and the description adds workflow-level behavior (everything in one call, no need to read rows and aggregate manually). However it says nothing about side effects, output size/pagination beyond the schema's limit default, or cost, and it does not resolve the surprising readOnlyHint=false/idempotentHint=false flags for what is functionally a query operation.

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, zero filler. The first sentence is front-loaded with the routing instruction (when to use this tool and which tools to avoid), and the second packs the operation set plus a do-not-workaround rule. Every clause 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?

With 9 parameters including nested objects and no output schema, the description covers selection/routing well but is silent on return shape, pagination behavior at the 100-row default, and error/edge cases (missing sheet, bad column). Given the annotations carry some safety signal, it is adequate but not complete for a parameter-heavy 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 description coverage is 78% and the schema already carries rich per-parameter detail (where-clause syntax example, group_by examples, aggregate alias semantics, limit default). The description restates the capabilities at a high level but adds no syntax or interaction detail (e.g. how select interacts with group_by) beyond what the schema provides, 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 names a concrete capability set — filter, group, aggregate, sort — over a concrete resource (any spreadsheet or CSV file path), and the title reinforces the row-level scope. It also implicitly separates itself from the generic row reader via 'never hand sums over sheet_read rows', so an agent can identify the right tool without opening schemas.

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 positive and negative routing: call this for any spreadsheet/CSV path, do NOT use the built-in file readers because they cannot parse spreadsheets, and do the aggregation here rather than summing sheet_read rows. Both the when-to-use and the when-not-to-use cases are stated with the alternative named.

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 the tool as read-only, idempotent, and non-destructive, so the description does not need to repeat safety traits. It adds useful behavioral context by explaining raw row reading, supported output formats, and pagination via limit/offset or an A1 range.

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 two tightly packed sentences: the first provides the critical routing rule, and the second summarizes output formats and pagination options. Every sentence contributes value with no repetition or 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 read tool with no output schema, the description gives enough to understand what it returns (rows as table, JSON, or CSV) and how to page through results. It does not specify the exact returned JSON/table shape or mention the sheet parameter, but the high-quality schema fills most of that 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 description coverage is high at 83%, and the schema already documents as, limit, range, sheet, and offset with defaults and override behavior. The description mostly echoes these concepts without adding meaningful new parameter semantics beyond clarifying that path refers to spreadsheet/CSV files.

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 a specific verb and resource: it reads rows from spreadsheet or CSV file paths and supports table, JSON, or CSV output. It distinguishes itself from built-in file readers, though it does not explicitly differentiate from sibling sheet tools such as sheet_query or sheet_load.

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 when-to-use rule ('Call this tool for any spreadsheet or CSV file path') and an explicit when-not-to-use rule for built-in file readers, which cannot parse spreadsheets. This is direct routing guidance with a named alternative class of functionality.

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

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

The description lists the statistics returned, providing some output expectation, but it does not state whether the operation is read-only, how errors like missing files are handled, or the response format. Annotations are all false, so they provide no safety or side-effect 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?

Two sentences carry the full message with no filler; the usage directive is front-loaded and the statistic list is compact. Every sentence 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?

Core purpose and output statistics are clear, but the definition is incomplete for an agent: it lacks sheet parameter semantics, output format, and read-only/side-effect guarantees. No output schema exists, so the description should carry more of this burden.

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%, and the description only adds meaning to path by allowing spreadsheet or CSV paths; columns already has a schema description. The optional sheet parameter is never explained, and no guidance is given about how it applies to CSV files.

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 identifies a specific operation: computing whole-column statistics (count, empty, distinct, min, max, sum, mean, median) for spreadsheet or CSV paths. It distinguishes the tool from built-in file readers, but it does not explicitly differentiate it from sibling sheet_* tools like sheet_read or sheet_query.

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

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

It explicitly says to call this tool for any spreadsheet or CSV file path and states that built-in file readers cannot parse spreadsheets and must not be used. This is clear usage context, though it does not discuss when to prefer sheet_query/sheet_read or when not to use this tool.

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

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

The annotations already signal a mutating, non-idempotent, non-open-world operation, so the description does not need to restate that. It adds useful behavioral detail beyond the annotations: "Other sheets are kept" clarifies side effects on existing workbooks, and "Free: 500 rows per file" discloses a quota constraint. No contradiction with the annotations is present.

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 three short sentences with no filler. It front-loads the core action, then packs the most decision-relevant facts—format selection, modes, preservation of other sheets, and row quota—into compact follow-up statements.

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 5-parameter write tool with a rich schema and no output schema, the description provides the key operational context: supported formats, mode choices, non-destructive effect on other sheets, and file-size limits. It does not describe the return value or error behavior, but the schema covers parameter semantics sufficiently for an agent to invoke the tool 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%, with detailed explanations for path, rows, mode, sheet, and out_path. The description mostly summarizes the mode enum and format selection rather than adding new meaning, so the baseline of 3 is appropriate; it does not need to compensate for schema gaps.

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: "write rows to an xlsx, csv, tsv or json file." It also clarifies that the output format is chosen by the extension of out_path, which distinguishes it from sibling read/query/convert tools. The name and title align tightly with this described behavior.

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 opens with "Call this tool to write rows," which gives a clear general context for when the tool applies. However, it does not name alternatives, state when not to use it, or explain how it differs from sibling tools like sheet_load, sheet_convert, or sheet_add_column. Usage is implied rather than explicit.

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