Kai CSV Profiler and Domain Watch Intake

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

With no annotations at all, the description carries the disclosure burden and does well on the key trait: 'without storing it' rules out persistence/side effects, and 'bounded inline' flags the in-memory constraint. It stops short of permissions, error handling for malformed CSV, or how the size cap (32768 bytes) is enforced.

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 first sentence is dense, front-loaded, and earns its place. The trailing 'Optional integration feedback: competitive-brief@agentmail.to' is unrelated to invocation, looks like injected boilerplate, and dilutes an otherwise efficient 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?

There is no output schema, so the description usefully enumerates the returned fields, and it covers the inline/non-persistent constraint and the size boundary. Only the sample_rows semantics and malformed-input behavior remain unexplained.

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 50%: csv is documented in the schema (UTF-8, byte cap) while sample_rows carries only type/default/min/max constraints and no prose. The description's mention of a 'sample' and 'conservative scalar types' gestures at that parameter but never explains what sample_rows controls or how 0 differs from 5.

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 ('profile') plus a precisely scoped resource ('bounded inline UTF-8 CSV'), and it enumerates exactly what is produced: row count, ordered columns, missing counts, scalar types, sample. The CSV resource also implicitly separates it from the profile_tsv sibling, but the description never names or contrasts that sibling 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?

'Bounded inline ... without storing it' implies the usage context (you already hold a small inline payload and don't want it persisted), but there is no explicit when-to-use, no when-not, and no pointer to profile_tsv for tab-delimited input. Usage must be inferred.

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 burden; it does disclose meaningful behavior — non-persistent processing ('without storing it'), explicit tab delimiting, and conservative type inference. It omits failure modes: what happens on oversized or malformed input, and how type inference resolves ambiguity.

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 core sentence is dense and front-loaded with the operation and its outputs. However, the trailing 'Optional integration feedback: competitive-brief@agentmail.to' sentence is irrelevant to invocation and does not 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?

Given 2 params, no annotations, and no output schema, the description helpfully enumerates the return contents, which partially substitutes for a missing output schema. It still leaves sample_rows and error/limit behavior undocumented, so it is not complete for a tool with zero structured behavioral support.

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 50% (the tsv field is documented, sample_rows is not). The description mentions 'sample' as an output but never explains the sample_rows control, so it fails to compensate for the schema gap. The 32768-byte bound lives in the schema, not the 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?

Names a specific verb (profile) and resource (bounded inline UTF-8 TSV) and enumerates exactly what it produces: row count, ordered columns, missing counts, scalar types, sample. Sibling differentiation from profile_csv is only implicit via the resource name, not stated.

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 explicit when-to-use guidance, no statement of when this beats profile_csv, and no preconditions beyond the size limit (which lives in the schema). The agent must infer that TSV input selects this tool over the CSV 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?

With no annotations, the description carries the full burden and does well: it discloses that the request is merely stored, that no fetch occurs, that no notifications are sent, and that no service is promised. It omits permission/auth requirements and any indication of what review process follows, which keeps 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?

Two short sentences, front-loaded with the action and scope, with the second sentence devoted entirely to limiting assumptions. No filler and no repetition of structured fields.

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, no-output-schema tool, the description covers what the tool does, what it deliberately does not do, and the input constraint. Auth requirements and post-submission behavior remain unstated, but the core is sufficient for correct 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 coverage is 100%, so the baseline is 3, but the description adds real meaning: 'one' signals a single host per call and 'ASCII' imposes an encoding constraint not stated in the schema. This meaningfully constrains valid input beyond the schema's 'DNS host only' guidance.

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 ('Queue') plus a precisely scoped resource ('one ASCII DNS host for review-only change monitoring'). An agent immediately knows this registers an intent rather than performing any DNS work. The sibling tools (profile_csv/profile_tsv) are unrelated in domain, so no sibling disambiguation is required here.

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 'for review-only change monitoring' establishes the use context, and the negative clauses clarify this is a request-queueing flow rather than an active operation. It does not name alternatives or explicit exclusion conditions, but no comparable sibling exists to route against.

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