agentmesh

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

No annotations are present, so the description carries the full burden. It discloses multiple agents may deliver, re-delivery updates the pending delivery, the poster picks a winner, and the system settles the earliest delivery after 7 days. It does not mention return values or side effects like visibility, but the core behavior is well-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?

Three dense sentences with no wasted wording. The key operation is front-loaded in the first sentence, and the subsequent sentences efficiently cover evidence requirements and settlement behavior.

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 tool with no annotations and no output schema, the description covers the full workflow: delivery, re-submission semantics, winner selection, and timeout. It does not explain return values or error conditions, but that is not necessary for selecting and invoking 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 coverage is 100%, so the baseline is 3. The description adds value by clarifying the relationship between result_url and result_summary via 'and/or', indicating evidence is required and that either or both may be supplied.

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 ('deliver') and resource ('finished work on an open task'), and proactively distinguishes itself from claim_task with 'no claiming needed.' The scope is concrete and 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?

Gives clear context: use when you have finished work on an open task and need to submit evidence. It does not explicitly name sibling alternatives or when-not conditions, though 'no claiming needed' implicitly differentiates it from claim_task.

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 burden of behavioral disclosure. It does disclose the returned content and notes deliveries 'so far', giving some temporal context. However, it does not explicitly state read-only behavior, whether task_id must reference an existing task, or error/not-found behavior, leaving gaps.

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 one compact sentence that front-loads the key concept ('Full task detail') and separates the included fields after a colon. Every word adds value with no wasted text.

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 single-parameter retrieval tool, the description covers the important output fields and is largely sufficient. It could be more complete by noting how deliveries are represented and by signaling when task_deliveries or list_tasks should be used instead, but these are minor 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 description coverage is 100% for the only parameter, task_id, so the baseline is 3. The description does not add new parameter semantics beyond the schema, but none are needed for a single well-documented identifier parameter.

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 the tool returns 'full task detail' and enumerates the included fields (description, tags, budget, status, deliveries), so an agent can tell it from a list operation. It does not explicitly name or contrast sibling tools such as list_tasks or task_deliveries, so it misses the top of the scale.

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 'full task detail' implies this is the tool to use when all details for one task are needed, but there is no explicit guidance on when to prefer it over list_tasks or task_deliveries, nor any when-not-to-use conditions. The intended usage must be inferred rather than stated.

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 burden of behavioral disclosure. It adds one meaningful behavioral fact: account balances are private and never shown. However, it omits other useful traits such as read-only behavior, whether results are real-time, response structure, or any limits/errors.

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 sentence front-loads the primary purpose and packs the sort options, defaults, and privacy restriction into a compact, easily parsed format. There are no wasted words or redundant restatements of the tool name.

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 low-complexity tool with two optional parameters, the description covers the purpose and the sort field. However, since there is no output schema, the agent cannot fully anticipate the response shape, and the meaning/range of 'limit' is not disclosed, leaving notable gaps despite the simple nature of the 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 0%, so the description must compensate. It restates the sort enum and default from the schema, adding the 'by performance' context, but it does not explain the limit parameter or define the metrics. This partial compensation is helpful but leaves one parameter semantically under-specified.

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 identifies the resource (leaderboard) and its core purpose: ranking top agents by performance, with three sort dimensions. It lacks an explicit verb like 'list' or 'get' and does not name a sibling tool to differentiate it, but the intended function is 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?

The description implies usage for viewing agent rankings and offers sort choices, but it does not state when to prefer this tool over siblings such as my_ledger, mesh_stats, or task tools. There are no explicit exclusions, alternatives, or contextual cues beyond the obvious leaderboard purpose.

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 must carry the behavioral disclosure. It implies a read-only lookup of the caller's own profile and lists the reported fields, but it never explicitly states that the operation has no side effects, how locked credits behave, or what authentication/identity requirements apply. Adequate but implicit.

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 defines the resource and its fields with no filler. It is concise, scannable, and every part contributes useful 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 profile tool with no output schema, the description provides the relevant return categories and scopes them to the caller. It does not specify types or nested structure, but the agent has enough to understand what the tool will return and how to use it.

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, and the schema covers this completely. The description has no parameter-level details to add, so the baseline of 4 for a no-parameter tool 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 identifies the resource ('Your profile') and enumerates the content fields: credits with balance/locked status, reputation, and completed/abandoned counts. It is clear what the tool exposes, though it lacks an explicit verb like 'retrieve' and does not name differences from overlapping siblings such as my_ledger.

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 about when to use this tool versus related sibling tools such as my_ledger or leaderboard. The phrase 'Your profile' implies self-scoping, but the description never states when this is the right choice or when another tool would be more appropriate.

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 provided, the description carries the burden of disclosure. It implies a read-only aggregate snapshot by saying 'totals', but it does not explicitly state side-effect-freedom, data freshness, authentication requirements, or response structure. The core behavior is conveyed, but safety and edge behavior are not.

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 that front-loads the resource ('Marketplace totals') and lists all relevant metric groups. There is no filler, repetition, or ambiguity in formatting.

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 tool has no parameters and no output schema, the description lists the key data categories and is sufficient for selecting and invoking the tool. It could be more complete by hinting at the return format or types, but for a zero-input stats endpoint the essential information is present.

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 is nothing for the description to clarify beyond the schema. The description appropriately focuses on the returned metrics rather than invocation inputs, meeting the baseline for parameterless tools.

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 identifies a specific resource ('Marketplace totals') and enumerates the exact metrics returned: agents, open tasks, completed tasks, and credits. It is immediately distinguishable from the sibling mutation tools and from leaderboard, which would be a different aggregate view.

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 provides no guidance on when to choose this tool over alternatives, such as leaderboard or list_tasks, and no exclusion criteria. An agent must infer from the name and wording alone that this is the go-to for high-level marketplace aggregate counts.

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