catchlog

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that every number is derived from stored entries and nothing is estimated, which tells the agent the output is deterministic. It says nothing about permissions, empty-logbook behavior, or result shape beyond the metric list.

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, metric scope front-loaded, and the second sentence adds a distinct trust guarantee rather than padding. Nothing is wasted.

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-param aggregation tool with no output schema, the description's enumeration of the returned dimensions (totals, longest, heaviest, per species/place/month) effectively stands in for a return-value spec. Minor gaps remain around empty results and permission requirements.

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, so there is nothing for the description to clarify; baseline 4 applies. No parameter-level semantics are needed or missing.

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 ('count') and resource ('your logbook') and enumerates the aggregations it produces (totals, longest/heaviest, per species/place/month). This is clearly distinguishable from list_entries (enumeration) and record_catch (write), 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?

Usage is implied: reach for this when you want statistics rather than raw rows. However, it gives no explicit when-to-use or when-not-to-use guidance and does not route the agent to list_entries for raw entries or record_catch for adding data.

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 are provided, so the description carries the full burden. It usefully discloses a scope constraint (other users' entries are never returned) and a result ordering, but says nothing about pagination behavior, rate limits, or the shape of returned entries.

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 zero filler, and the core scoping/ordering facts are front-loaded. 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?

For a simple read-only list tool with one schema-documented parameter and no output schema, the description covers what it returns, its ordering, and its ownership scope. Only pagination and return-format details are absent, which is a minor 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 coverage is 100% and the single limit parameter is already fully documented in the schema (default 20, max 100). The description adds no syntax or default information beyond that, 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 (List) and resource (entries in your own logbook) plus the ordering (newest first), so the agent knows exactly what comes back. It does not explicitly name or distinguish itself from the siblings catch_summary and record_catch, which keeps it short of a 5.

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: the tool is clearly for viewing your own entries, but there is no statement of when to prefer it over catch_summary or record_catch, and no exclusions or prerequisites. Adequate but with a clear gap in routing guidance.

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 are provided, so the description carries the full burden. It usefully discloses the two outcome shapes ('the stored entry, or the list of errors that prevented storing it'), which tells the agent writes may fail and how failure surfaces. It says nothing about permissions, whether a failed validation discards everything, or whether entries are mutable/deletable, leaving gaps for a no-annotation mutation tool.

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, no padding, with the purpose front-loaded ahead of the return-behavior note. 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 no output schema, the description correctly summarizes both success and validation-error returns, and it names all the required fields plus most optionals for a nine-parameter tool. The omission of 'notes' and any behavioral note about the write itself is a minor 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 the schema already documents all nine parameters with formats and units; baseline 3 applies. The description groups the required fields and lists the optional ones, adding light framing, but misses 'notes' entirely and adds no meaning beyond the schema.

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 ('Record one catch in your logbook') and enumerates the fields being captured, which distinguishes a write operation from the read-oriented siblings catch_summary and list_entries. However, it never names those siblings, so the differentiation is inferred rather than explicit.

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 implied by 'record one catch' — the agent can infer this is the logging tool used before catch_summary or list_entries would be relevant. There is no explicit when-to-use statement, no mention of the sibling tools as alternatives, and no stated preconditions.

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