feellab-mcp

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

With no annotations, the description carries the full burden of behavioral disclosure. It does add one useful behavioral detail: the result is 'every problem, or none,' indicating an exhaustive error report. However, it does not state whether the tool is read-only, what permissions it needs, or how the problems are formatted, leaving significant gaps for a check 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?

The description is extremely short, but it is not a complete sentence and omits essential information for invoking the tool correctly. Its brevity reflects under-specification rather than disciplined conciseness.

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 the absence of annotations, output schema, and schema parameter descriptions, the description should carry much more of the context. It communicates the tool's broad intent and a hint about the return value, but is missing usage guidance, parameter clarification, and behavioral details needed for confident 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 description coverage is 0%, and the single 'path' parameter is undocumented in both the schema and the description. The description mentions 'a timeline file' but never explains what the path parameter should point to or how it is interpreted, so it 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?

The description identifies the resource (a timeline file) and the contract (feellab-timeline/1), and the tool name 'check_timeline' supplies the verb. It is clear enough for an agent to distinguish from siblings like list_checklist or judge_folder, though the description itself is a fragment rather than a complete statement.

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 alternatives, nor any preconditions or exclusions. The description only states what it checks, leaving the agent to infer the appropriate context entirely.

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 and no output schema exist, so the description carries the full behavioral burden, and it only partially meets it by naming four row columns. It says nothing about whether this is a read or write, permissions, errors on missing folder/subject, or pagination.

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, which is structurally fine, but the brevity is under-specification rather than discipline — the sentence is too short for a tool with two required, undocumented parameters.

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 annotations, no output schema, and 0% parameter coverage, the description should explain inputs and behavior, but it explains neither. The 'Weapon Lab row format' reference is unexplained jargon an agent cannot act on.

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 0% with two required parameters (folder and subject), and the description never explains what either accepts. The bare word 'subject' appears only inside the row-format list, not as parameter guidance, so the agent gets no semantic help for its two mandatory inputs.

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 resource ('metrics as rows for a gate') and hints at the row shape, so the agent knows roughly what is produced, but it is a noun phrase with no verb and never distinguishes itself from the sibling list_metrics or judge_folder. It reads more like an output-format note than a statement of what the tool does.

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 when-to-use guidance, no prerequisites, and no mention of when to prefer this over list_metrics or judge_folder. An agent must guess from the name alone which sibling to call.

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 at all, the description carries the full behavioral burden. It does disclose one meaningful side effect - a Markdown report is 'written beside' the input files - which is real context beyond the schema. However, it omits whether judging requires an LLM/API cost, permissions, whether outputs overwrite existing reports, and where exactly files land, leaving significant gaps for a write-producing 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?

It is a single, front-loaded sentence with a colon-enumerated output list and no filler. The phrasing is slightly fragmented/grammatically loose, but nothing is wasted and the key action leads.

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 must carry the return-value burden - and it does list the judged artifacts and the Markdown report. But for a complex judging tool with no annotations and an undocumented optional parameter, it stops short of the behavioral and routing context an agent would need to invoke it confidently.

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%: 'folder' is documented in the schema, but the optional 'subject' parameter has no description anywhere. The phrase "Each subject's scenes" hints at the subject concept but never explains that 'subject' is a filter parameter or what format it takes, so the description fails to compensate for the coverage gap.

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 real action (judging scenes) and its resource (a folder of subject/scene timelines), and enumerates the outputs: measured values, rules, verdict, summary, and a Markdown report. This is clear enough for an agent to understand intent, but it never distinguishes itself from close siblings like check_timeline or gate_rows, which the agent must pick between.

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 statement of when to use this tool versus the alternatives (check_timeline, gate_rows, list_scenes). No prerequisites, no input assumptions, no exclusion criteria are given, so the agent must infer placement among siblings on its own.

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. It discloses the shape of the content (interaction, expected result, verification type) but says nothing about read-only nature, permissions, pagination, or result format. For a listing tool with zero annotation coverage this is a notable gap.

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 padding. It is slightly awkwardly phrased, but every clause earns its place by describing checklist content.

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 partially compensates by sketching the return content, which is the main gap. It still fails to explain the group filter's domain (what A–J correspond to) or confirm the operation is a safe read.

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% — the single group parameter is documented as 'A to J, or leave out for all'. The description adds no additional meaning about what a group represents, 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 the resource (the checklist) and describes its contents — every interaction, expected player outcome, and verification method — which is more informative than a bare restatement of the name. However, there is no explicit verb and no differentiation from siblings like list_scenes or list_metrics, so an agent must infer that this is a read/list 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?

There is no when-to-use guidance, no mention of the optional group filter, and no routing to or away from the sibling list tools. The agent is left to guess when this checklist view is preferable to list_scenes or list_metrics.

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. It does disclose the shape of each returned record (scene, unit, direction, rule, rule source), which is genuine value, but it says nothing about side effects, permissions, pagination, or volume limits.

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 telegraphic sentence with no filler, and the scope ('Every metric') is front-loaded. It reads as a fragment rather than a complete sentence, which slightly hurts readability but wastes no 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?

No output schema exists, so describing the returned fields is exactly the right content, and it covers the salient ones for a metric. Missing details are minor: ordering, pagination, and whether any filtering is possible.

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 the baseline is 4. There is no parameter semantics for the description to clarify or omit.

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 the resource and its scope ('Every metric') and enumerates the attributes returned, so an agent knows this is an unfiltered enumeration of metrics. It does not differentiate from siblings like list_scenes or list_checklist, but the name and returned fields make the purpose unambiguous.

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, no when-not-to-use, and no mention of alternatives among the sibling list tools. The only clue is the word 'Every', implying an unfiltered dump, but the agent must infer that.

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 of behavioral disclosure. It does not state that the tool is read-only, does not mention return format, ordering, pagination, or any side effects—only vaguely alludes to scene contents.

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 a single sentence fragment that is under-specified rather than genuinely concise. It does not front-load a verb or action, and the sentence structure lacks the clarity expected of a tool description.

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 list tool with no output schema and no annotations, the description should at least state that it returns a list and describe the return structure. It hints at scene contents ('one timeline each, and what each asks it to do') but omits the fundamental action and return format, leaving it incomplete.

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 has zero parameters, so there are no parameter semantics to document. The baseline score for a no-parameter tool is 4 according to the rubric.

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 is a noun phrase ('The standard scenes a probe plays...') that defines the content of the scenes but never states an action like 'Lists' or 'Returns'. It does not clearly distinguish this tool from siblings such as list_checklist or list_metrics, and it reads more like a data definition than a tool purpose.

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, when not to use it, or which alternatives exist. The description provides no context for selection among the sibling list tools.

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