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

No annotations are provided, so the description carries the full burden. 'Introspect' signals a non-mutating read, and because there is no output schema, naming the returned fields (column types, PKs, FKs) is genuinely valuable. But it says nothing about behavior on a missing table or whether views/indexes are covered.

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

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

One sentence, front-loaded with the verb and terminated by the concrete return fields. No waste, though the bare enumeration reads slightly like a field list rather than prose guidance.

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

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

For a two-parameter read-only introspection tool with no annotations and no output schema, the description covers the essential shape of what comes back. The gaps are edge-case behavior (nonexistent table, views) rather than anything blocking a correct call.

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

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

Schema description coverage is 100% and both parameters are documented there, so the description adds nothing. It never mentions db_path or table_name, leaving format expectations (relative vs absolute path, schema-qualified names) entirely to the schema, which is minimal.

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 ('Introspect') plus resource ('table') and enumerates exactly what is surfaced: schema, column types, primary keys, foreign keys. That enumeration implicitly separates it from list_tables and execute_query, 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?

Usage is only implied by the verb: an agent would reasonably infer 'call this before writing a query against an unfamiliar table.' There is no explicit when-to-use, no statement of preferred alternative (e.g., list_tables to discover names first), and no prerequisites.

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 no annotations, the description carries the full behavioral burden, and 'with safety constraints' is an unelaborated claim — it never says which constraints (multi-statement blocking, write gating, transaction behavior, error shapes). For a tool that can mutate a database, the side effects, reversibility and permission requirements are undisclosed.

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

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

A single front-loaded sentence with no redundancy. However, the trailing phrase 'with safety constraints' is vague filler that signals a capability without describing it, so it doesn't fully earn 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?

A mutation-capable, four-parameter tool with no annotations and no output schema needs the description to cover safety behavior, write-mode consequences and result shape. None of that is present, leaving the agent without enough context to invoke it safely.

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 are already documented in structured data, and the description adds no syntax, format or interaction detail beyond it. Baseline 3 applies since the schema does the heavy lifting.

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 (execute) and resource (SQL query) and notes both read-only and read/write modes. It never names a sibling, so an agent must infer that it should not use this for schema inspection (list_tables/describe_table) or plan analysis (explain_query). Clear purpose, but no explicit 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?

There is no guidance on when to use this tool versus list_tables, describe_table or explain_query, and no guidance on when to flip read_only to false. Usage is only implied by the verb. The read_only default is documented in the schema but the description doesn't explain the tradeoff.

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 no annotations, the description carries full burden. It implies a non-mutating analysis step, which is the key behavioral trait versus execute_query, but never states that the query is not actually executed, nor anything about permissions, cost, or safety. It adds partial behavioral signal only.

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

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

A single front-loaded sentence with no filler; every clause earns its place. It is arguably too terse for what it must convey, but it is not padded.

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 and no annotations, yet the description says nothing about what the EXPLAIN QUERY PLAN result looks like (plan rows), nor that the query is only analyzed rather than run. For an analysis tool whose output the agent must interpret, this leaves a meaningful 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 100%, so both db_path and query are already documented in the schema. The description adds no format guidance, e.g. whether query may contain parameters or multiple statements. 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 specific verb ('Get') and a precise resource ('SQLite EXPLAIN QUERY PLAN analysis') with a stated purpose (optimize indexing). It is clearly distinct from list_tables and describe_table, though it never explicitly contrasts itself with execute_query, the closest sibling.

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 phrase 'to optimize indexing' implies the use case (query performance tuning), but there is no explicit statement of when to prefer this over execute_query or what preconditions apply. Usage is inferable rather than guided.

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?

No annotations provided, so the description carries the burden. 'List' implies a read-only operation and it discloses the return content (tables, views, row counts), which is useful. It does not say whether row counts are exact or estimated (which can be expensive on large DBs), whether system/internal tables are included, or anything about permissions.

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

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

A single front-loaded sentence that names the resource and the returned fields with zero filler. Nothing could be removed without losing 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 one-parameter read tool with no output schema, the description covers what is returned and the environment (SQLite). Minor gaps remain around row-count cost and inclusion of internal tables, but an agent has enough 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 coverage is 100%, so db_path is already documented as a path to the SQLite file. The description adds no further meaning such as whether the path must exist or how relative paths resolve, so the schema does all the work.

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 (List) and enumerates exactly what it returns: tables, views, and row counts in a SQLite database. This naturally separates it from describe_table and execute_query, though it never names those siblings 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?

No guidance on when to call this versus describe_table, execute_query, or explain_query, and no prerequisites or exclusions are stated. The agent must infer that this is the discovery step before describe_table.

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