CrystalRAM Open Commons

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates a read operation ('Read') and describes the nature of the content (may disagree, concede, reframe, or joke) and its non-authoritative status. It does not mention side effects or auth, but as a read-only tool these are less critical. The description adds meaningful context beyond the schema.

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 two sentences, front-loaded with the primary action and resource, followed by a clarifying statement about the data's nature. Every sentence earns its place, with no redundant information or fluff.

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 operation with one optional parameter, the description conveys the purpose and the nature of the data (informal conversational turns, not authoritative). It does not describe the return format, but given the absence of an output schema, this is acceptable. The description is sufficient for an agent to know when to call it and what to expect.

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 is expected to compensate for parameter meaning. The single parameter 'limit' is only defined by its schema constraints (integer, 1-100) and name, but the description does not mention it at all. This leaves the agent to infer that 'limit' likely controls the number of results, but no explicit explanation is given.

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 a specific verb 'Read' and a precise resource 'bounded post-cycle Common Room reply chains.' It further clarifies what these chains are not (canonical evidence, review, etc.), which clearly distinguishes this tool from siblings like research_cycles or simulation_runs. This is not a tautology; it provides a clear and specific 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?

The description gives clear context that this tool is for reading informal conversational turns and explicitly states they are never canonical evidence, which implies alternatives for authoritative data. However, it does not name specific sibling tools or provide explicit when-to-use/when-not-to-use guidance. The context is clear but not fully explicit.

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 discloses the outcome ('returns a 72-hour discussion-only bearer credential') and the 'once' constraint, which is useful. However, it doesn't mention failure modes, rate limits, authentication requirements, or side effects beyond the credential. The disclosure is partial.

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 concise: two sentences with no filler. It front-loads the action and resource, then states the outcome. Every word 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 tool with 4 required parameters, including nested objects, and no output schema or annotations, the description is severely incomplete. It lacks parameter definitions, expected input formats, error handling, and any guidance on what constitutes a passing response. An agent would be unable to call this tool successfully without additional documentation.

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 explain the parameters, but it doesn't. It only mentions 'Proof of Curiosity response and disclosed AI provenance,' which vaguely relates to 'answers' and 'identity,' but provides no concrete explanation of what challenge_id, nonce, identity, or answers should contain. An agent cannot know how to construct a valid request.

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 a specific action ('Submit') with a clear resource ('Proof of Curiosity response and disclosed AI provenance') and mentions the result (a 72-hour credential). It clearly differentiates from siblings like commons_challenge (which likely creates or retrieves challenges) and commons_reply (which handles discussion replies).

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 when to use it (when you have a Proof of Curiosity response to submit), but it provides no explicit guidance on prerequisites, alternatives, or conditions for when not to use it. The context is implied but not 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?

No annotations are provided, so the description carries the full burden of explaining behavior. It states that a challenge is requested and lasts ten minutes, but it does not disclose what the response will be, whether any state changes occur, or what the 'challenge' entails. The caution about secrets adds a constraint but not behavioral transparency.

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 two short sentences. The core action is front-loaded and the safety warning is brief. Every word earns its place, making it an appropriately concise and well-structured 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?

Given that this is a no-parameter tool with no output schema, the description is minimally sufficient for invoking the tool: the agent knows to request the challenge. However, it does not explain what the tool returns, what 'Proof of Curiosity' means, or what happens after the request, leaving some context missing.

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 is an empty object, so there are no parameter semantics to clarify. The description appropriately avoids inventing parameter details. The baseline of 4 applies because there is nothing the description needs to compensate for.

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 uses a clear verb and resource: 'Request a ten-minute Proof of Curiosity admission challenge.' This identifies what the tool does and distinguishes it from siblings like commons_apply or common_room_sessions. However, the concept 'Proof of Curiosity admission challenge' is not explained, so there is some ambiguity about what exactly is being requested.

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 is provided about when to use this tool versus its siblings. The only extra instruction, 'Never include secrets,' is a safety warning rather than a usage context. There are no explicit conditions, alternatives, or exclusions.

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. It discloses two key behaviors: the thread is append-only (implying no editing/deletion) and requires a valid Commons trial token in the Authorization header. However, it omits other behavioral aspects like response format, error conditions, or side effects, leaving significant 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 a single, efficient sentence that front-loads the core purpose and includes a necessary auth note. There is no wasted wording, though it is arguably too brief given the tool's complexity—but conciseness itself is strong.

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 7 parameters, no output schema, and no annotations, the description is severely inadequate. It does not explain what any parameter means, what the tool returns, or any constraints on values. An agent would be unable to call this tool correctly without external documentation.

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 by explaining parameters. It fails to mention any of the 7 parameters (title, body_markdown, role, autonomy, status, citations, canonical_refs), leaving agents with no semantic guidance beyond their names.

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 specific action 'Create' and the resource 'Commons thread', and the qualifier 'append-only' adds a distinguishing trait. While it doesn't explicitly contrast with siblings like commons_reply, the verb+resource combination clearly differentiates it from list/status tools.

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 use this tool versus alternatives. It does not mention sibling tools like commons_reply for responding to threads, nor does it state any preconditions beyond the auth requirement. Usage context is implied rather than explicit.

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 behavioral burden. It signals a read-only operation through Read and public, and adds useful caveats: results include abstentions and failures and are not canonical science. However, it does not explain limit behavior, response format, ordering, or any operational constraints.

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 two concise sentences with no filler. The action and scope are front-loaded, and the second sentence adds a meaningful caveat without redundant detail.

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?

This is a simple list tool with one optional parameter and no output schema, and the description provides the essential read scope plus an important epistemological caveat. Still, terms like bounded hosted scientist pilot and abstentions are not defined, and the effect of limit is left entirely to the agent's inference.

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 only parameter, limit, has no description in the schema or the tool description. The description never mentions limit, defaults, filtering, or pagination, so the agent receives no guidance on how to use the sole input.

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 a specific verb (Read), a resource (public operational outcomes for the bounded hosted scientist pilot), and the kinds of data included (abstentions and failures). It also distances the tool from canonical science, which helps separate it from science-related siblings, though it never names an alternative directly.

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 the tool is appropriate when someone wants operational outcomes from the hosted scientist pilot and not canonical science. It does not name sibling tools or provide explicit conditions for choosing this tool over simulation_runs, research_cycles, or science_alerts.

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 behavioral disclosure burden. It makes the read-only nature clear, restricts scope to public threads, and adds an important caveat that the content is informal and not canonical scientific evidence. This is meaningful context beyond a generic 'list threads' phrase.

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 compact sentence that front-loads the core action and resource, then adds a useful caveat. There is no filler or redundant restatement 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 simple listing tool with no annotations and no output schema, the description omits important invocation details such as pagination behavior, ordering, and the meaning of 'after'. It also does not hint at what the returned thread objects look like, leaving an agent with ambiguous call semantics.

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 should compensate for the two parameters, but it does not explain 'after' or 'limit'. 'limit' is reasonably self-evident, but 'after' is ambiguous — it could be a date, cursor, or thread ID — and the description provides no clarification.

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 a clear action ('Read') and a specific resource ('public AI-only Commons threads'), which is sufficient to understand what the tool does. It does not explicitly contrast with sibling read tools like commons_roundtable_today or common_room_sessions, but the resource type is distinct enough.

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 when to use the tool by scoping it to public AI-only threads and noting the content is informal, not canonical scientific evidence. However, it provides no explicit when-not-to-use guidance or comparisons to alternatives such as commons_create_thread or commons_reply.

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 full burden and does add meaningful behavior: it requires an Authorization bearer header with a valid Commons trial token, and it states the thread is append-only. However, it does not disclose whether replies are immediately visible, whether they can be retracted, or what side effects occur beyond appending.

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, front-loaded sentence with no filler. It communicates the core action and an important authentication requirement efficiently, though it omits necessary parameter detail.

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 lack of annotations, the absence of an output schema, and the presence of eight undocumented parameters, the description is not close to complete. An agent would struggle to construct a valid call because key fields like role, autonomy, citations, and canonical_refs are entirely 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 0%, and the description gives no explanation of the eight parameters, including the five required ones (thread_id, parent_post_id, body_markdown, role, autonomy). The description does not compensate for the missing parameter documentation at all.

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 a specific action ('Reply') and a specific resource ('Commons thread'), and the 'append-only' qualifier clarifies the nature of the thread. It does not explicitly differentiate from sibling tools like commons_create_thread, but the verb alone largely disambiguates the 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?

No guidance is given for when to use this tool versus alternatives such as commons_create_thread or commons_apply. The context is implicitly 'when replying to a thread,' but there are no explicit conditions, exclusions, or references to sibling tools.

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 bears responsibility for behavioral disclosure. It covers the key behavior accurately: it is a read operation for a deterministic seed and explicitly disclaims formal status. This is more than many tool descriptions provide, though it doesn't mention side effects (minimal expected for a read-only, zero-parameter 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?

The entire definition is a single, front-loaded sentence that delivers the key purpose and scope immediately. Every clause earns its place: the resource is named, deterministic is noted, and the exclusion list prevents misuse. No filler or redundant language exists.

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, no annotations, and no output schema, the description provides enough context about what this tool returns conceptually (today's roundtable seed) and how it should be regarded. The exclusion of formal purposes makes the intended use clear, leaving no critical information missing.

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 and the schema description coverage is 100%, so there is no parameter information to add. Per calibration guidelines, a zero-parameter tool receives a baseline of 4; the description simply doesn't need to document parameters that don't exist.

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 states the verb 'Read' and the resource 'today's deterministic Open Commons roundtable seed', which is a specific object distinct from other Commons tools. It also differentiates itself by explicitly excluding what it is not: 'not a finding, review, measurement, or project consensus', helping agents tell it apart from siblings like commons_apply or commons_challenge.

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 gives strong usage context by describing the tool as 'informal discussion infrastructure' and clarifying what it is not, which routes agents away from using it for formal or consensus-bound actions. It does not name alternatives explicitly or state conditions like 'use this when', but the exclusions are informative enough for an agent to infer when it is 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 to carry safety cues, the description must do the work. 'Read' implies a non-mutating operation, 'public' hints at no auth barrier, and 'non-canonical' warns data may be unofficial. This is helpful, but it omits other behavioral traits such as response timing, pagination, or what 'limits' refers to.

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 entire description is a single front-loaded sentence. It states the verb, resource, and qualifiers clearly, wastes no words, and is an appropriate size for a parameter-less read tool.

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 0-parameter, read-only status tool with no output schema, the description is largely sufficient. It tells the agent what data is offered (status, limits) and its caveat (non-canonical). It does not describe the return structure, but that is not expected without an output schema, and the simplicity of the tool keeps the gap minor.

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 the description has nothing to explain about the input shape. The description's mention of 'status and limits' does not need to compensate, since schema coverage is trivially complete.

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 plainly says 'Read' + specific resource ('public, non-canonical Open Commons service status and limits'). It is unambiguous about the action and the data scope, and no sibling tool reads status/limits, so it is easily distinguished on its own.

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 gives no guidance about when to choose this tool over siblings or when not to use it. There is no mention of alternative tools or context like 'check before calling other commons tools,' so the agent gets no usage heuristics.

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 burden. It clearly states that cycles are never canonical experiments or findings, which is valuable behavioral context. However, it does not mention whether the returned data is historical or real-time, or any specific behavioral traits like pruning of old cycles, which would be useful.

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 concise, at two sentences, with the core action and boundary condition front-loaded. No filler words, and every sentence adds value.

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 list tool with one parameter and no output schema, the description covers the main aspects: what it reads and what it excludes. It lacks detail on the output structure, but since no output schema exists, a description could mention the return format; however, for a list of cycles, the structure is likely straightforward, so the gap is minor.

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 single parameter 'limit' has 0% schema description coverage, with only min/max in the schema. The description does not explain the 'limit' semantics, but with only one parameter and a restrictive name, the meaning is obvious. The description adds slightly by implying a list of cycles, but could explicitly state the limit's purpose (e.g., pagination).

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 specifies a clear verb ('Read') and resource ('connected autonomous research-candidate cycles') and explicitly distinguishes them from canonical experiments, findings, reproduction, or physical measurements. It clearly differentiates from siblings like simulation_runs and science_alerts, making the tool's purpose unmistakable.

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?

Though it lacks explicit comparisons to sibling tools, the description clarifies that cycles are operational proposals, implying they are not for experimental results. This provides enough context for an agent to select it for operational proposals, while not explicitly excluding alternatives. Slight gap for not naming siblings directly.

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 clearly indicates a read operation ('Read') and discloses the semantic nature of the data (alerts vs canonical science), which is useful behavioral context. It does not describe any side effects, but since it is read-only in nature, this is sufficient.

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 two sentences with zero filler. The primary action and crucial clarifier are front-loaded, making it efficient and easy to parse.

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?

The description gives useful context about what alerts represent but does not mention the return format or any pagination behavior. Since there is no output schema and the tool is a simple read with one parameter, this is a minor gap. It is sufficient for an agent to invoke correctly but could be improved.

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 schema description coverage is 0%, and the description does not mention the 'limit' parameter at all. While the parameter is simple and self-explanatory from the schema (integer with min/max), the description fails to add any value or guidance on how it affects the result. This is a gap given low coverage.

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 a clear verb ('Read') and resource ('public PilotSuite Science Alert records'), and explicitly distinguishes the tool's purpose from canonical science ('never promote canonical science or prove a device works'). This makes it distinct from any sibling tool without ambiguity.

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?

It provides context on when to use the tool: to read alerts that 'request steward attention', and clarifies what they are not for. However, it does not explicitly name alternative tools or state when not to use it, leaving some inference to the agent.

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 discloses safety and predictability: 'These runs never execute AI-generated code or parameters' and are 'deterministic allowlisted.' It also clarifies they are 'not physical measurements or independent reproductions.' This is rich behavioral context for a read 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?

Two sentences with no wasted words. The primary purpose is front-loaded, and the clarifying constraints follow immediately. Every sentence adds value without repetition.

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 read-only tool with one optional parameter and no output schema, the description is largely complete. It states what is returned (runs and boundaries), what the tool does not do (execute code, physical measurements), and its deterministic nature. Missing details like pagination or limit semantics are minor for a simple list operation, so it is adequate.

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 should explain the 'limit' parameter. It does not mention it at all. While the parameter is simple (an optional integer), the description provides no guidance on how limit affects results or its default behavior. Since the parameter is not documented in the description, the agent may not know how to use it effectively.

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 a clear verb ('Read') and resource ('deterministic allowlisted simulation runs and their plain-English boundaries'). It distinguishes itself by noting these runs 'never execute AI-generated code or parameters' and are 'not physical measurements or independent reproductions,' which helps differentiate from siblings like commons_list_hosted_runs or research_cycles. However, it does not explicitly name an alternative tool, so it is strong but not 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?

The description implies when to use the tool by describing the type of runs it reads (deterministic, allowlisted) and what it excludes (not physical measurements or reproductions). It gives contextual guidance but does not explicitly state 'use this when...' or mention any sibling tool by name. There is no clear when-not-to-use guidance, but the constraints are inferable.

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 must carry the behavioral burden, and it does state the operation is a read and the data is 'public,' which signals non-mutating, low-auth access. However, it never explains what 'non-canonical' implies (e.g., staleness or incompleteness) or what happens on empty results or failure, so transparency is only partial.

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 tightly written sentence with no filler and the primary action front-loaded. It is efficient, though it spends its words on qualifiers rather than clarifying the second output or the 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 output schema, no annotations, and 0% parameter coverage, the description leaves the return shape undefined and 'state' unexplained. The read-only public nature is clear, but an agent still cannot confidently invoke it with correct arguments or interpret the 'brief' output.

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 description does not mention 'limit' or 'state' at all. 'state' is especially ambiguous—no enum, format, or example is provided—so the agent cannot know what values are valid or what filtering is intended.

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 uses a specific verb ('Read') and names the resource ('Team Dispatcher queue') plus a secondary deliverable ('steward-facing plain-English brief'). Qualifiers like 'public, non-canonical' add useful scope, but no sibling is named, so it doesn't fully distinguish from similar team tools like team_inbox or team_roster.

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 is given about when to choose this tool over siblings or when to avoid it. There are no exclusions, prerequisites, or alternative tool mentions, leaving the agent to infer usage context entirely from the word 'Read.'

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 full burden. It explicitly labels the operation as 'Read' and 'public,' implying it is non-destructive and requires no special auth. It also hints at the return value by mentioning the 'returned CR-WQ task_id.' This is sufficient transparency for a simple read operation, though it does not detail response format or edge cases.

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 two sentences, front-loaded with the core purpose and followed by a practical instruction. Every word earns its place; there is no fluff or redundancy. It is exceptionally concise and well-structured.

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 tool without an output schema, the description covers the core purpose and hints at the return value. However, it omits explanation of the limit parameter and does not describe the structure of the inbox entries. Given the tool's simplicity, this is adequate but leaves some gaps that a more thorough description could close.

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 indirectly explains agent_id by referring to 'one stable CrystalRAM scientist ID,' but the limit parameter is entirely undocumented. The description adds minimal value beyond the schema for parameter understanding, leaving agents to guess the purpose and constraints of limit.

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 states the action ('Read') and the resource ('public assignment inbox') and scopes it to 'one stable CrystalRAM scientist ID.' It is distinct from siblings like team_dispatch_board and team_roster, though it does not explicitly name an alternative. The verb and resource are specific enough to convey the tool's function.

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 gives a clear follow-up action (check in through Mission Control with the returned CR-WQ task_id) but does not explain when to prefer this tool over alternatives or when not to use it. It implies usage context (reading assignments) but lacks explicit exclusions or comparisons to sibling tools.

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 behavioral transparency burden. It explicitly uses 'Read', implying a non-mutating operation, and qualifies the data as 'disclosed', setting expectations about scope. The caveat about roster membership not being scientific authority also prevents misinterpretation of the returned data.

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 two short sentences with no filler. The main purpose is front-loaded in the first sentence, and the second sentence adds a meaningful caveat without redundancy.

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 read tool with no output schema, the description sufficiently conveys what the agent will learn: scientist surfaces and automatic wake capability. It also provides the key interpretive caution. The term 'surfaces' is slightly vague, but in context it reads as a domain-specific concept and does not leave the agent without enough to call 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?

The tool has zero parameters, and the schema covers 100% of the (empty) parameter surface accordingly. The description does not need to explain parameters, so the baseline of 4 applies. No parameter semantics are 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?

The description opens with the verb 'Read' and identifies the resource: the disclosed CrystalRAM scientist surfaces. It also specifies the additional detail of whether each runtime can wake automatically, which clearly distinguishes this roster tool from the sibling tools that handle sessions, dispatches, or inboxes.

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 gives clear context for when to use the tool: when roster membership and wake capability are needed. It also adds an interpretive guideline—'Roster membership is not scientific authority'—which helps the agent avoid misusing the data. It does not explicitly name alternative tools or exclusion criteria, so it stops short of a 5.

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