NodeLoc MCP

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools target distinct actions and resources, with clear boundaries between topic listing, node membership, chat, points, and payments. A few pairs like get_user_profile vs get_user_summary or list_latest_topics vs list_top_topics could cause minor hesitation, but descriptions generally make the differences clear.
Naming Consistency3/5
The set uses recognizable patterns for many groups (list_*, get_*, create_*, payment_*, docs_*), but mixes read verbs inconsistently: get_current_user, list_latest_topics, read_topic. Some actions are unprefixed like checkin, and payment tools use prefix-noun while most others use verb-noun, so the naming is readable but not uniform.
Tool Count2/5
With 42 tools, the server exceeds the threshold where a tool set feels heavy and hard to navigate. The broad domain explains part of the size, but many tools are granular variants that could be consolidated without losing clarity.
Completeness3/5
The server covers a wide range of community features: topics, posts, PMs, nodes, chat, points, payments, and docs. However, there are notable gaps such as no topic search, no update/delete for topics or posts, no node update/delete, and no chat channel discovery or management, leaving important workflows incomplete.
Average 3.5/5 across 42 of 42 tools scored. Lowest: 2.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- Last stable release on August 30, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description is the sole source of behavioral transparency. 'Like a post' merely restates the action and does not disclose whether the operation is idempotent, whether it changes the like count, whether it requires authentication, or what happens if the post is already liked. This is a major gap for a state-changing write action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no filler or repetition of schema details, and the core action is front-loaded. It is concise, though arguably too thin, but the conciseness itself is good.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 should carry more context. It omits authentication expectations, idempotency, return behavior, and any interaction with the existing like state, so an agent cannot predict the outcome of repeated calls or failures. Only the schema's required post_id provides invocation detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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, but it does not mention post_id at all. That said, the sole parameter's name and type (post_id integer) make its role inferable from the description's 'post' noun, so the missing documentation is less harmful than for a multi-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names the verb ('Like') and the target ('a post') unambiguously, and the action is clearly different from siblings like unlike_post and bookmark_post. However, it is essentially a restatement of the tool name and does not explain the effect of a like or differentiate it from other engagement actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus unlike_post or bookmark_post. There is also no mention of prerequisites, such as authentication requirements or whether the post must already exist. The only contextual clue is the tool's name, which is not enough to route an agent confidently.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only says 'Bookmark a post' and does not explain side effects, idempotency, authentication requirements, or what a bookmark represents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single terse sentence with no wasted words, making it easy to parse. However, it is so minimal that it omits important context, so it is concise more than appropriately informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 is too thin to fully guide an agent. The agent is left without information about behavior, when to use it, or any side effects, even though the parameter set is simple.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter schema has 0% description coverage, and the description adds no meaning beyond the property name 'post_id'. While the schema already tells us it is a required integer, the description does not clarify how to obtain the ID or any constraints on it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear action ('Bookmark') and a specific resource ('a post'). It is distinct from sibling tools like like_post and unlike_post, though it does not explicitly name or differentiate from those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as like_post, give_reward, or other post interactions. The description does not mention any exclusions, prerequisites, or conditions for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only states that the user can leave a node, but does not explain whether this removes membership, is reversible, requires permissions, or has side effects on the user or the node.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no wasted words and gets straight to the action. It is concise, though the brevity comes at the cost of omitting useful behavioral and parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even though the tool has only one required parameter and no output schema, the description leaves important operational context missing: it does not describe the effect of leaving, where node_id comes from, or how this relates to join_node. It is barely more informative than a stub.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema lists a single integer node_id with 0% schema description coverage, and the description does not mention node_id at all. There is no explanation of what node_id represents, how to obtain it, or its role in the leave operation, so the description adds no parameter-level meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('Leave') and the resource ('node', glossed as 'nested community'), making the tool's intent easy to recognize. It does not explicitly name sibling tools like join_node, but the verb itself communicates the core purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives such as join_node, list_nodes, or create_node. No conditions, preconditions, or exclusion criteria are provided, so the agent must infer routing entirely from the name and one-line description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 signals a mutating action but does not disclose whether retracting is idempotent, what happens if no vote exists, whether only the current user's vote is affected, or whether poll tallies are updated immediately. This is a material gap for a writelike operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one short, direct sentence with no redundancy or filler. Its brevity is appropriate for a simple operation, though it is near the edge of being under-specified rather than elegantly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, this single phrase leaves several correctness-relevant unknowns: error behavior when no prior vote exists, whether the action is reversible, and what response is returned. Given `vote_poll` exists as a sibling, a brief note contrasting when to call `unvote_poll` vs `vote_poll` would meaningfully improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning beyond the raw parameter names `post_id` and `poll_name`. While `post_id` is relatively self-explanatory, `poll_name` is ambiguous, and the description does not clarify whether it is a poll title, key, slug, or other identifier. Description does not compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'retract' and names the resource 'poll vote', making the action clear and semantically distinct from the sibling `vote_poll`. It does not explicitly name the sibling, but the inverse relationship is obvious enough to differentiate the tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 relative to `vote_poll` or other vote-related siblings. UNLESS context implies un-voting, there is no mention of prerequisites such as having already voted, nor is there any when-not advice. The phrase 'retract' gives an implied use case but not explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states only that messages are fetched, but does not mention pagination behavior with page_size, ordering, permissions, or what the response contains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler or redundant phrasing. It earns its place by stating the action and the exact containment relationship in few words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, 0% schema coverage, no annotations, and no output schema, this description is too sparse. It leaves page_size, return format, and the distinction from get_chat_messages unaddressed, so an agent would have to infer important calling details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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, but it only loosely hints at channel_id and thread_id via the nouns 'channel' and 'thread'. The page_size parameter is entirely unexplained, and no parameter formats or constraints are given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Fetch') and a specific resource ('messages of a chat thread inside a channel'), which makes the tool's purpose understandable. It differentiates the resource from the similar sibling get_chat_messages by emphasizing 'thread', but it does not explicitly contrast the two tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to choose this tool over get_chat_messages or other chat-related tools. The description simply states what it does, leaving the agent to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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, but it only says the tool creates a node. It does not mention side effects, prerequisites (e.g., existing parent category), validation behavior, uniqueness constraints on slug, or what the response contains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely compact with no filler. The purpose sentence is front-loaded and the only additional sentence points out an optional parameter, so both parts earn their place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating tool with five parameters, no annotations, and no output schema, this description is severely incomplete. It omits the semantics of all required parameters, expected behavior on failure, return value, and any dependencies such as a valid parent category.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 20% because only color is documented in the schema. The description repeats that color is optional but adds no meaning for the four required parameters: name, description, slug, and especially parent_category_id.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Create a new node') and clarifies the domain term with '(nested community)', which differentiates it from other creation tools such as create_topic or send_private_message. The purpose is immediately understandable to an agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives, when not to use it, or which sibling tools cover related cases like listing nodes or checking a slug. An agent must infer applicability solely from the name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'Join' implies a mutating action, but the description does not explain the effect on membership, whether the action is reversible, whether it is idempotent, or what happens if the user already belongs to the node.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler and the main action is front-loaded. It is appropriately brief for a one-parameter tool, though the terseness limits the amount of useful context conveyed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is minimally viable: an agent can infer that it should call this tool with a node_id to join a node/community. However, with no annotations and no output schema, the description leaves gaps around expected behavior, prerequisites, and possible error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only the parameter name and type (node_id as integer), with 0% description coverage. The description adds context by identifying the node as a nested community and implying that node_id is the target node, which is close to sufficient for a single integer parameter, though it does not explicitly define valid ID values or scope.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Join') and a resource ('a node', glossed as a nested community). It is distinguishable from sibling tools like leave_node and create_node, though it does not explicitly name alternatives or define what joining entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as leave_node or create_node. No preconditions, exclusions, or authentication requirements are mentioned, so the agent must infer usage solely from the verb.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'Query' suggests a read-only operation, but the description does not mention authentication requirements, idempotency, error behavior, potential rate limits, or whether it only works for transactions created through the same Payment API.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short, front-loaded sentence that communicates the core action and domain with no filler. Every word contributes meaning, and the parenthetical is a useful clarifier rather than redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one required parameter, so the schema plus the short description may be enough for basic invocation. However, the lack of output schema, absence of annotations, and missing guidance about what status values are returned or how the transaction ID is obtained leaves notable gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema declares a single required string transaction_id, but the description does not explicitly mention the parameter or explain its format, origin, or relation to payment_create/payment_transfer. The phrase 'payment transaction' weakly implies what transaction_id refers to, but with 0% schema description coverage, this is minimal compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Query') and a specific resource ('status of a payment transaction'), and the parenthetical 'official Payment API' adds domain context. It is clearly distinguishable from 'payment_create' and 'payment_transfer' by the status-query intent, though it does not explicitly name or contrast with those siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as after calling payment_create or payment_transfer, or how it relates to other payment-related operations. There are no exclusions or conditions stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing side effects, permission requirements, or send constraints. It only states the action and the recipients format; it does not mention authentication needs, whether this is a write/mutation operation, rate limits, or any expected outcome. This is a significant gap for a communication-sending tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the primary purpose. It does not waste words, and the recipients clarification is useful, though it duplicates the schema. It is appropriately concise but could have used the available space to add behavioral or usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three required parameters, no annotations, and no output schema, this description is under-specified. It omits when to use it, how it relates to send_chat_message, what a successful send returns, and any prerequisites. An agent has only the bare action and a parameter hint, which is not enough for confident invocation in a real workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67%, and the description only repeats the recipients meaning already present in the schema. It adds no meaning for 'title' or 'raw' beyond their types, and the Markdown body description is already in the schema. The baseline of 3 is appropriate because the schema does most of the work, but the description gives no extra value for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The phrase 'Send a private message' states a specific verb and resource, clearly distinguishing the core action from topic creation or chat messaging at a basic level. It doesn't explicitly differentiate from sibling tools like send_chat_message, but the action is unambiguous enough for an agent to know 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as send_chat_message or create_topic. It gives no context about audience, privacy semantics, or situations where a private message would be appropriate, leaving the agent to infer usage entirely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries full responsibility for behavioral disclosure. It only states what the tool does ('Vote in a poll') without explaining effects like whether an existing vote is overwritten, whether votes can be changed, idempotency, or required authentication. This is a significant gap for a mutating operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loads the core action in the first sentence. The parameter note is minimal and targeted. It earns full conciseness but loses structure points for not expanding on required parameter semantics.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating tool with three required parameters, no output schema, and no annotations, this description is incomplete. It does not explain how post_id and poll_name identify the poll, what options values are accepted, what the response indicates, or what happens on repeat votes. An agent would need additional information to confidently use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33%, with only 'options' documented. The description repeats the 'options' meaning but adds no detail about post_id or poll_name, leaving two required parameters semantically unexplained. The description fails to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Vote in a poll attached to a post') and identifies the resource (a poll attached to a post). It is distinct from sibling tools like unvote_poll by the verb 'vote', though it does not explicitly differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when a user wants to vote in a poll attached to a post. However, it provides no explicit guidance about alternatives, such as unvote_poll for removing a vote, or any conditions or prerequisites for voting.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries behavioral disclosure. It usefully adds that the request is 'Anonymous' and that filter is typically 'latest' or 'top'. However, it does not disclose pagination behavior, default filter handling, or what the response contains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded; the action appears immediately and every sentence carries some information. It could be more formally structured, but there is no wasted prose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 4-parameter tool with no output schema and no annotations, the description leaves defaults, response shape, pagination behavior, and sibling-tool routing implicit. An agent can make a basic call but may not know what to expect back or when to choose another tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 75% and the schema already documents slug, category_id, and filter. The description adds only 'typically' for filter values and leaves the page parameter entirely unexplained, so it provides marginal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource ('List topics in a category'), which makes the core purpose clear. It distinguishes itself from global topic lists by the 'in a category' scope, but does not explicitly name any sibling tool like list_node_topics for direct differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance about when to prefer this tool over list_latest_topics, list_top_topics, or list_node_topics. The filter note is parameter-level advice and 'Anonymous' is an auth condition, but neither explains the selection criteria or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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, but it only states the action without mentioning side effects, error conditions, idempotency, or required authentication. This is a notable gap for a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one succinct sentence with no redundant words. It front-loads the action and the object, making it immediately understandable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but with no annotations and no output schema, the description omits return values, failure behavior, and preconditions. More context is needed for an agent to invoke it correctly in real scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description's use of 'post' indicates that post_id refers to the target post, adding minimal meaning. However, it does not explicitly explain the post_id parameter's semantics or any constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Remove') and a clear resource ('like from a post'), making the action unambiguous. It also naturally distinguishes itself from the sibling like_post, so an agent can identify which operation to invoke.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as like_post, or any mention of prerequisites like requiring an existing like. The context is only implied by the name and the description, leaving the agent to infer the appropriate scenario.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral burden. 'Anonymous' usefully discloses auth expectations and 'Get' implies a non-mutating operation. However, it does not describe the response shape, data freshness, error behavior, or whether any user can be looked up.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. The core purpose is front-loaded, the parenthetical clarifies scope, and 'Anonymous' is an efficient behavioral note.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read tool, the description covers the main purpose and auth context. But with no output schema, no annotations, and no guidance about when to prefer this over sibling tools, the overall picture is only minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage and only a bare 'username' string property. The description's 'a user's activity summary' adds little meaning beyond the property name; it does not explain username format, case sensitivity, or how missing/invalid usernames are handled.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Get a user's activity summary' with explicit contents '(posts, likes, badges)'. This makes the tool's function clear. It does not explicitly contrast itself with siblings like get_user_profile or get_current_user, but the activity-summary focus is still distinctive enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'Anonymous,' which implies this can be called without authentication and provides some usage context. However, it lacks any explicit guidance on when to choose this tool over alternatives like get_user_profile or search_users, and no when-not-to-use conditions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the entire behavioral burden. It indicates only that a reply will be made with a Markdown body, but does not disclose side effects (e.g., publishing a new post, notifications), authentication requirements, or error/return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short, front-loaded sentence with no filler. The parenthetical and optional clause add useful operation details without bloating the text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple three-parameter tool, the core call is understandable and enough to select it, but the absence of annotations and output schema leaves notable gaps around side effects, permissions, and return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 33% schema coverage, the description must compensate. It clarifies that raw is a Markdown body (redundant with the schema) and that reply_to_post_number selects an optional specific post, but it does not describe topic_id beyond the word 'topic.'
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Reply to a topic') and adds two relevant details: the body is Markdown and a specific post number can optionally be targeted. It does not explicitly compare itself to sibling tools such as create_topic, so it stops short of full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied: when an agent wants to post a reply to an existing topic, this is the tool. No when-not-to-use guidance or explicit alternatives are given, even though create_topic and send_private_message are close siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must bear the full burden of behavioral disclosure. It identifies the mutation ('send') but does not mention required permissions, side effects, rate limits, failure modes, or response behavior, which are relevant for a chat-sending action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence with no filler. The core action and the optional thread behavior are front-loaded, and every word contributes to the agent's understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple three-parameter send operation, the description is mostly sufficient, but with no annotations and no output schema it omits potentially useful context such as whether thread_id must belong to the specified channel, delivery guarantees, and what the agent should expect as a response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 does clarify that channel_id is the target channel and thread_id enables optional threading, and it implies message is the content. However, it adds little beyond what the parameter names and types already suggest.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a clear verb and resource: sends a chat message to a channel, optionally into a thread. This distinguishes it from send_private_message and reply_to_topic, though it does not explicitly name or contrast any sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 specifying channel-based chat and optional threading, but it gives no explicit guidance on when to prefer send_private_message or reply_to_topic instead. This is adequate for such a simple tool, but not strongly directive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 that results are paginated, which is a meaningful behavioral trait, but it does not explain pagination mechanics, ordering, read-only status, or any other side effects. This is partial but minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes meaning, and the pagination note is efficiently placed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read-only fetch, the description is minimally viable: it names the resource and indicates pagination. However, it omits what the response contains, how pagination is controlled, and any usage caveats, leaving the agent to infer important details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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, but it only hints that channel_id identifies the chat channel. page_size is completely unexplained beyond being an integer, adding little semantic value for an agent selecting parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Fetch messages') on a specific resource ('a chat channel'), and explicitly notes pagination. This distinguishes it from the sibling get_chat_thread_messages, which operates on threads rather than channels.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives such as get_chat_thread_messages, send_chat_message, or mark_chat_read. The context is only implied by the resource name, not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 implies a value transfer but does not state that points are deducted from the caller, whether the action is reversible, whether sufficient balance is required, or any failure/rate-limit behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler. It communicates the core purpose immediately and contains no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating tool with no annotations and no output schema, this description is too thin. It explains what the action is but not the consequences, requirements, or response behavior, so an agent lacks important context for correct and safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sentence gives implicit meaning to post_id ('the author of a post') and amount ('energy points'), but at 0% schema coverage it still leaves the optional note parameter semantically unexplained. The description partially compensates for the schema, but not completely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific action ('Tip'), a resource ('energy points'), and a target ('the author of a post'). It clearly distinguishes this from sibling read/mutation tools like like_post or bookmark_post because transferring points is a distinct operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context for use is implied: reward the author of a post. However, there is no explicit guidance about when to prefer this over related tools such as payment_transfer or create_red_envelope, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. 'List' suggests a read-only operation and 'inside a node' clarifies scope, but it does not mention pagination behavior, return shape, or whether the listing includes nested subnodes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. The parenthetical '(nested community)' adds relevant disambiguation, though the overall terseness contributes to the lack of parameter guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, no annotations, low schema coverage, and four parameters, this one-line description is incomplete. An agent is left without clear guidance on required parameter semantics or expected return data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25%, with only the sort parameter documented. The description adds the useful clarification that a node is a 'nested community,' but it does not explain slug, node_id, or page semantics, leaving most parameters under-specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'List topics inside a node (nested community).' This clearly differentiates the tool from siblings like list_latest_topics and list_top_topics, which are not scoped to a node.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: when topics within a specific node/nested community are needed. However, it does not explicitly contrast with alternatives such as list_category_topics or list_latest_topics, nor does it state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 does state the important default behavior of using the logged-in user, but it does not explicitly describe read-only status, permission implications, or behavior when a username is supplied. It is not misleading, but it is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no filler. The essential scoping information—what is retrieved and who it defaults to—is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple query tool with one optional parameter, the description covers the resource and the default behavior adequately. It leaves some details unspecified, such as behavior when a username is explicitly provided and the exact return format, but nothing critical prevents correct tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines username as a string with no description. The tool description adds meaning by stating that it defaults to the logged-in user, which clarifies that the username parameter is optional and that omitting it selects the current user. This meaningfully compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Get energy points income/expense history.' It clearly identifies what the tool returns and the logged-in-user default. It does not explicitly differentiate from the sibling get_points_scores, but the resource phrasing is specific enough for an agent to infer the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use or when-not-to-use guidance is provided, and no alternative tools are mentioned. The default-to-logged-in-user note is contextual but does not help the agent decide between this tool and similar points-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only repeats the list operation and gives content categories; it does not state whether listing notifications changes read state, whether it is read-only, or what response shape to expect. Given the sibling mark_notifications_read, the read-state behavior is a meaningful unspecified trait.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One short sentence with a parenthetical category list; every word earns its place and the core resource and scope are front-loaded. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple parameterless list operation, the description is mostly complete: it identifies the resource, user scope, and notification types. It is not fully complete because it omits return/read-state behavior, but the lack of an output schema and parameters lowers the burden.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters and 100% schema coverage, there is no parameter ambiguity for the description to resolve. The description appropriately adds no parameter text, matching the baseline for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource ('List notifications') and scopes it to the logged-in user, listing included categories. It is not a tautology and is clearly distinct from topic/message tools, though it does not explicitly differentiate itself from the sibling list_private_messages, which also involves PMs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for the logged-in user' provides a clear context, so an agent can infer this is the current user's notification feed. However, there is no explicit guidance on when to choose this over mark_notifications_read or list_private_messages, and no when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. 'Anonymous' is a useful auth-related behavior, and 'List' implies a read-only operation, but no further details are given about output format, ordering, limits, or side effects. It adds some value but leaves notable gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short, purposeful fragments: the action statement and the anonymity note. It is front-loaded with the core verb and resource, with no filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter list action, the description is largely sufficient. 'Anonymous' covers the main contextual prerequisite, and the tool name plus description make the expected return type (topics) clear. However, the criteria for 'top/trending' are not defined, which could matter in some contexts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is trivially complete at 100% coverage. The description does not need to explain parameter meaning, and the baseline of 4 applies. Nothing is missing in this dimension.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'List top/trending topics.' The phrase 'top/trending' implicitly distinguishes this from siblings like list_latest_topics and list_category_topics, though it does not explicitly contrast with them. It is clear enough for an agent to understand the core function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus list_latest_topics or list_category_topics. The 'Anonymous' note hints at authentication requirements but does not address selection criteria, sorting, or alternatives. An agent is left to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It states the core effect (marks a chat channel as read) and the threshold behavior (up to a message id), which is useful. However, it does not disclose permission requirements, idempotency, or whether the operation is reversible or affects unread counts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with zero filler. The operation and its key parameter semantics are conveyed immediately, and no sentence is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, and the description covers the core operation and main parameter roles. However, with no annotations, no output schema, and no usage or alternative guidance, the definition leaves some context gaps that could affect an agent's confidence in selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 for parameter meaning. It does connect channel_id to 'chat channel' and message_id to the 'message id' read threshold, but it does not clarify whether the message_id is inclusive/exclusive, how the channel is identified, or any constraints beyond what the schema's types imply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('mark') and resource ('chat channel') and adds the precise threshold 'up to a message id'. This clearly distinguishes it from sibling tools like mark_notifications_read, which operates on notifications rather than chat channels.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention mark_notifications_read or any other sibling, nor does it describe conditions or exclusions. Usage context is only implied by the tool's name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the disclosure burden. It does reveal a behavioral trait by stating the default user, but it does not describe output format, authentication requirements, or limitations. The verb 'Get' implies read-only but does not explicitly guarantee it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One short sentence, front-loaded with the action and resource, and no filler. It earns its place despite being terse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-optional-parameter read tool, the description is minimally callable, but it lacks an output schema and any note on limits or response shape. An agent would still be uncertain what 'breakdown' includes or how it differs from get_points_history.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the username parameter has no schema description, but the description compensates by indicating the default behavior: 'defaults to the logged-in user' implies the optional username parameter overrides the target user. This is enough to infer the parameter's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action and resource: 'Get energy points score breakdown' and adds a scope detail, 'defaults to the logged-in user.' It does not explicitly distinguish itself from sibling get_points_history, so it stops 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'defaults to the logged-in user' phrase implies the tool is for fetching points breakdowns, optionally for another user, but no when-to-use or alternative guidance is given. With a large sibling list including get_points_history, explicit differentiation would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden. It states the operation is 'Anonymous' and accesses 'public' data, which clarifies authentication and access-level expectations. It doesn't cover error behavior or explicitly state read-only semantics, but the verb 'Get' makes that reasonably clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no wasted words. The primary purpose is front-loaded, and 'Anonymous.' earns its place by conveying authentication behavior. This is an ideal size for a simple single-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only profile tool, the description covers the core essentials: what is returned (trust level, bio, stats), that the data is public, and that no authentication is needed. There is no output schema, so the return-content hints are valuable. It doesn't mention edge cases like missing usernames, but that is a minor gap for this level of complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 for parameter meaning. It does not explain the username parameter's format, requirements, or how it maps to the returned profile, leaving the agent to rely on the parameter name alone. The name 'username' is self-explanatory, so this is not a 1, but the description adds little value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource: 'Get a user's public profile' and lists the key contents (trust level, bio, stats). It is clear and distinguishable from get_current_user, but it does not explicitly differentiate from similar siblings like get_user_summary or search_users.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case: fetch a public profile by username, and 'Anonymous' suggests it can be used without authentication. However, it provides no explicit guidance on when to choose this tool over get_current_user, get_user_summary, or search_users.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral context. It discloses that the operation is anonymous and that page numbering starts at 0, which is useful. It does not describe response shape, result limits, ordering details, or any error/rate-limit behavior, but for a simple read-only list tool this is a reasonable baseline.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences convey purpose, authentication context, and pagination behavior without filler. The most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter, read-only list tool, the description is mostly complete: it states what is listed, where, authentication status, and page starting value. It could additionally state the shape of the returned topic objects or page size, but these are not essential to invoking the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters and already describes page as an integer starting at 0. The description only restates this same meaning and adds no deeper semantic detail, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb and resource: listing the latest topics on the forum homepage. It is distinguishable from siblings like list_top_topics and list_category_topics because of the homepage and latest orientation, though it does not explicitly name those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives useful usage context: this is the anonymous homepage-latest listing, and pagination starts at 0. It does not explicitly state when to prefer this over list_top_topics or list_category_topics, 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.
Behavior3/5
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 the core behavior and outcome: a payment request is created and the buyer must open the returned payment_url to pay. It does not disclose authorization requirements, side effects, idempotency, or failure behavior, which would be valuable for a payment tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, and the most important facts are front-loaded: the action, the API family, and the return value. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The return value is explained, which helps compensate for the missing output schema. However, there is no annotation coverage, no guidance on required authentication, no explanation of the `description` parameter, and no mention of how to follow up on the payment, so the description is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes `amount` and `order_id`, and the description only repeats the `order_id` meaning. The required `description` parameter has no schema description and the tool description does not explain what should go in it, leaving an important parameter semantically unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Create a payment request') and identifies the official Payment API. It also explains the key output ('Returns a payment_url'), which clearly separates this from read-only payment tools like payment_query or money-moving tools like payment_transfer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The tool's context is implied: use it when you need to create a payment request that the buyer pays via the returned URL. However, it does not explicitly explain when to prefer it over payment_transfer or mention when not to use it, leaving routing to the agent's inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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, yet it only repeats the creation operation and parameter hints. It does not mention authentication, side effects, return values, failure behavior, or the fact that this is a mutating action that could create public content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short, front-loaded sentence with a terse supplementary note about parameter sources. Every word earns its place, and there is no filler or redundant elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The essential invocation data—required params and the source of `category_id`—is present, and the schema covers parameter details. However, there is no output schema and no description of what the API returns or what happens after creation, leaving the agent without guidance on expected results or possible side effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 three parameters well. The description adds only a lightweight restatement that `raw` is Markdown and that `category_id` should be obtained from `get_site_info`, which matches the schema rather than meaningfully extending it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with the specific verb+resource pair 'Create a new topic,' making the tool's purpose immediately unambiguous. It also clarifies that `raw` is Markdown and that `category_id` comes from `get_site_info`, which reinforces the resource context and differentiates it from reply/private-message tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Create a new topic' clearly signals the primary use case, and the instruction 'category_id from get_site_info' provides a concrete prerequisite for invocation. It does not explicitly call out exclusions or compare with siblings like `reply_to_topic`, but the guidance is clear enough for the intended use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 explains that the tool lists topics and defaults to the logged-in user, but it does not mention authentication requirements, read-only guarantees, pagination, or whether querying another user's private messages is permitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It states the action, the resource, and the default behavior efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read tool, this is adequate but not complete. The absence of annotations and output schema means the description should ideally clarify return shape, pagination, and privacy/auth boundaries; those details are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for the optional username parameter, but the description meaningfully explains it: it identifies the target user and clarifies that omitting it defaults to the logged-in user. This compensates for the bare schema, though it could add constraints like username format or permission limits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and a specific resource ('private-message topics of a user'), and it adds the useful default-scope detail ('defaults to the logged-in user'). This clearly separates it from siblings like send_private_message and list_notifications.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives some usage context by explaining the default user, but it does not state when to prefer this tool over alternatives such as list_notifications or get_user_profile. No exclusions or alternative tool names are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 non-obvious requirement of a pre-existing login and implies the environment is non-interactive, which is useful. However, it does not state whether commands can create or modify resources, what output is returned, or how failures surface, leaving significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two efficient sentences: it fronts the action, then gives examples, prerequisites, and cwd definition. There is no filler, and each clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description never explains what the tool returns (stdout/stderr, exit codes) or how to interpret command failures. For a generic CLI runner with open-ended commands, this is a significant completeness gap; an agent cannot predict the result of 'submit' or 'playtest'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters, so the schema already explains 'command' and 'cwd'. The description's example arguments ('init my-app', 'playtest', 'submit') merely echo the schema examples and add no new semantic information, keeping this at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('Run') and a specific resource ('official nodeloc-apps CLI command for in-site miniprograms'), and provides concrete examples ('init my-app', 'playtest', 'submit'). It is clearly distinct from all sibling tools, which cover forum, payment, and docs operations rather than executing a universal CLI.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states concrete prerequisites (CLI installed, logged in) and flags that interactive login must be performed manually in a terminal, which tells an agent when the tool is ready to use. It does not explicitly name an alternative because no sibling offers the same capability, but the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. 'List' implies a read-only operation, and 'my memberships' implies user-scoped data, but the description does not explicitly state side effects, authentication requirements, pagination, or whether nested nodes are returned recursively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless listing tool with no output schema, the description is largely complete: it names the resource and the user-scoping. It could briefly note the return shape or any pagination/recursion behavior, but these are minor gaps given the low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and the schema confirms this with 100% description coverage. The description adds useful context about what is being listed, which is sufficient for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('all nested communities (nodes) and my memberships'), and it is clearly distinct from sibling tools like list_node_topics or create_node. An agent can immediately understand what this tool returns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as list_node_topics or get_current_user. There is no mention of context, exclusions, or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It does disclose meaningful behavior beyond the schema: the total points are split into shares and only users who reply can claim them. However, it omits side effects, authentication requirements, potential limits, or what happens after creation, which would be expected for a mutation tool without annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence with no filler. It is front-loaded with the verb and resource, and the explanatory clause directly follows. Every part of the sentence earns its place by explaining either the action or a key parameter behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The task is simple (three integer parameters), and the description explains the core mechanics adequately. However, there is no output schema and the description does not indicate whether the tool returns a confirmation, the created envelope object, or an error message. Given that no annotations or output schema are present, a bit more detail about the outcome of the operation would make this more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It does this well by attaching semantics to the parameters: total_points means 'energy' to distribute and total_count means the number of 'shares' to split into. The topic_id is contextualized via 'in a topic'. This provides an agent with the meaning needed to correctly populate the parameters, though it stops short of fully describing each parameter in isolation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific verb ('Create'), the resource ('a red envelope in a topic'), and the core mechanic ('total_points energy split into total_count shares, claimable by users who reply'). This makes the tool's purpose distinct from all siblings, including give_reward, which might otherwise seem similar. No ambiguity remains about what action this tool performs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the obvious use case: when an agent needs to create a red envelope for topic respondents. However, it provides no explicit guidance on when not to use this tool or which sibling alternative might be more appropriate in other scenarios. The usage context is inferable but not directly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for disclosing behavioral traits. It states 'Anonymous', which signals that no authentication is required—a useful transparency note. 'Get' implies a read-only operation with no side effects, but the description does not explicitly confirm this or mention any rate limits, caching, or variability in the returned configuration.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two short phrases—and front-loads the primary action ('Get site configuration') before details and access mode. Every word earns its place; the only minor weakness is the vague 'etc.', but the overall structure is exemplary for a simple getter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema and only a brief description, the agent cannot fully predict the shape or breadth of the response beyond 'categories (id/name/slug)'. For a simple, zero-parameter tool this may be adequate, but 'etc.' leaves room for ambiguity about what other configuration fields exist (e.g., site name, logo, settings). The absence of explicit return-value documentation lowers completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema provides no meaningful constraints. Per rubric, the baseline is 4. The description adds helpful information about the return payload (categories with id/name/slug), which further compensates for the lack of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('site configuration'), with concrete examples of the returned data ('categories (id/name/slug)'). It clearly distinguishes this tool from sibling tools by indicating it returns global site configuration rather than user or topic-specific data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: when you need site configuration or category metadata. However, there is no explicit guidance about when not to use it or which alternative tools might be better suited for related but distinct purposes (e.g., list_category_topics for category-specific content). The mention of 'Anonymous' provides some usage context but no exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and meaningfully discloses non-obvious behavior: the sender pays a trust-level-based fee, the operation is idempotent per order_id, and to_user_id/to_username must match. It does not cover error/reversal behavior, but core side effects are transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two dense sentences with no filler. The primary action is front-loaded, and the constraints are packed efficiently. Every clause adds value: direction, official API, identity consistency, fee, and idempotency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description covers the essential operation, constraints, fee, and idempotency, which is a solid minimum. However, it omits return/error behavior, auth expectations, and what happens if the identity constraint is violated, so it is not fully complete for a financial mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25% (order_id documented), so the description must compensate. It adds that to_user_id and to_username must refer to the same user, and implies amount is in energy points. But it leaves to_user_id/to_username formats and amount bounds mostly to inference, so gaps remain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Transfer energy points from the payment-app owner to a user' via the 'official Payment API.' It clearly differentiates this from siblings like payment_create and payment_query, which describe different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended usage is implied: use this to transfer energy points from the owner to a user. However, it does not explicitly contrast with payment_create/payment_query or state when not to use it. The mention of 'official Payment API' gives context but not clear alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only says the tool searches by name/username and gives examples; it does not explain matching behavior, result limits, pagination, required permissions, or what the response contains. This is minimal and leaves significant behavioral assumptions to the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with no filler. The action, resource, searchable fields, and use cases are all front-loaded and every word contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter search tool, the description is mostly complete: it explains what to pass and why. The main gap is that without an output schema it does not describe the result shape, but for a straightforward user search this is a minor omission.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters but only describes 'term' as 'Search term'. The description adds meaning by clarifying that the term matches name or username, which is more informative than the bare schema. For a single-parameter tool this is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Search') on a specific resource ('users') with clear search fields ('by name/username'). This distinguishes it from profile-retrieval siblings like get_user_profile, which fetch a known user rather than resolving an unknown one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The examples 'to resolve @mentions or PM recipients' give concrete contexts where this tool is appropriate. It does not explicitly state when not to use it or name alternatives, but the intended use case is clear enough for an agent to select it over sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the behavioral disclosure burden. It clearly states the core effect (marks notifications read) and the scope (all vs. single), but it does not mention authentication needs, idempotency, or what happens to already-read notifications. These are not covered by annotations, leaving some behavioral context implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler. The main action is stated first, and the optional-parameter condition is appended concisely. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter mutation tool, the description is mostly sufficient for invocation, but because there are no annotations and no output schema, it leaves gaps: it does not describe the return value, and 'all notifications' is ambiguous about whether that means the current user's notifications or a global scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only a type for notification_id with no description, so the description must add meaning. It does this well by explaining that presence of notification_id scopes the operation to a single notification and absence scopes it to all. It doesn't define the ID's origin, but that's reasonably inferable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('mark'), a clear resource ('notifications'), and a target state ('as read'), and it further distinguishes all-notifications mode from single-notification mode via notification_id. This makes the tool's purpose unambiguous and separates it from read/list tools like list_notifications and mark_chat_read.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
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 and explains the conditional: omit notification_id to mark all, provide it to mark one. It does not explicitly state when not to use it or name alternatives, so it falls just short of full usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 adds useful behavioral context by stating the response contains trimmed HTML bodies and that the operation is anonymous. This goes beyond the tool name, although it does not cover error behavior 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one short sentence that is front-loaded with the main action and includes only necessary additional details. No redundant phrases or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity, full parameter schema coverage, and the fact that the description states the response contains the topic and its posts (with trimmed HTML bodies), the description is complete enough for an agent to invoke the tool correctly. There is no output schema, but the description covers the relevant return content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents topic_id as an integer with the description 'Topic id', and schema description coverage is 100%. The tool description confirms that the topic is being read but does not add extra meaning beyond the schema for the single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies a clear verb (read), resource (topic), and output scope (topic with posts, trimmed HTML bodies). This distinguishes it from the list-oriented sibling tools (list_latest_topics, list_top_topics) because it targets a single topic by id.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when you need one topic and its posts. However, it does not explicitly state when not to use it or name alternatives, such as list_latest_topics for browsing multiple topics or list_category_topics for category-scoped listing. The usage context is clear but implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden of disclosure. 'Check whether... available' implies a non-mutating read operation, but the description does not explicitly state that no changes are made, nor does it mention authentication or response behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no redundant wording; the purpose and usage context are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter check with no output schema, the description provides sufficient context about what to check and when to use it. It could mention the exact return value, but 'available' reasonably implies a boolean result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the schema only says 'slug' is a string. The description provides additional meaning by identifying it as a node slug and explaining the parameter's role in availability checking.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and resource ('node slug') and explicitly ties it to the pre-creation workflow ('before creating a node'). This clearly distinguishes it from mutation/read siblings such as create_node or list_nodes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'before creating a node' gives a clear temporal usage context, telling the agent to call this as a preflight step. It does not name alternatives or exclusions, but for a single-purpose check the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses that the tool returns Markdown content and accepts flexible page identifiers, which is useful. However, it does not mention failure behavior for missing pages, authentication requirements, or output size limits, leaving some behavioral uncertainty 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler. The primary purpose and output format are front-loaded, and the parameter guidance is compact and directly actionable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema or annotations, the description covers the essential information: what the tool returns and what forms the input can take. It could additionally mention error behavior or how to discover page identifiers, but the current description is adequate for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines `page` as a string with 0% description coverage, so the description must compensate. It does so by explaining that `page` can be a full URL, a path like 'energy/checkin', or a title fragment from docs_list_pages. It stops short of detailing exact matching rules or ambiguous-title handling.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly names the action ('Fetch') and the resource ('a knowledge-base page'), and specifies the output format ('as Markdown'). It also distinguishes this tool from sibling listing/search tools like docs_list_pages and docs_search by focusing on retrieving a single page's content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear invocation context by explaining that `page` can be a full URL, a path, or a title fragment from docs_list_pages. It does not explicitly contrast this tool with docs_search or state when not to use it, but the 'Fetch a page' framing makes the appropriate use case reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden, and it does add one meaningful behavior: body matching is limited to cached bodies. But it does not disclose pagination, result ordering, or read-only safety, and gives no return-shape expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no filler; every phrase ('by keyword', the field list) carries selection and invocation value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter search tool with a clear purpose, the description is nearly complete. It could mention whether search is exact/substring and what it returns, but those are not blockers for an agent deciding to call it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only declares keyword as a string with 0% coverage; the description compensates by defining the keyword as matching titles, descriptions, and cached bodies. It does not specify match semantics, but for a one-string parameter the agent has enough to make the call.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Search' with the knowledge base as the resource and lists the searched fields (titles, descriptions, cached bodies), which clearly distinguishes it from sibling tools like docs_get_page or docs_list_pages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'by keyword' supplies the main use condition, and the field list says what will be matched, so an agent knows when to call it. It does not explicitly name alternatives or state when not to use it, so it falls 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It clearly states that the tool enumerates all pages and exactly which fields are returned, making the operation's behavior predictable for a simple parameterless read.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence contains the verb, resource, scope, and output fields with no filler. The most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless list operation with no output schema, the description is complete: it says what is listed, the scope, and the fields returned. An agent can invoke the tool and understand the result without needing additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. There is nothing for the description to add beyond confirming that the operation takes no inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('List'), a unique resource ('all pages of the NodeLoc knowledge base'), and the returned fields (title, url, description). This clearly distinguishes it from the sibling tools docs_get_page and docs_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for retrieving the full page list, but it does not explicitly state when to use it instead of docs_get_page or docs_search. The usage context is inferred from the word 'all' rather than explicitly articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It discloses the daily limit and the server's response to repeated calls, which are the key non-obvious behaviors. It could also mention authentication requirements, but the core behavioral traits are covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences deliver the essential information with no filler. The action is front-loaded, and the behavioral constraint follows immediately. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description covers the essential facts: what it does, how often, and what happens if called again. It is slightly incomplete in that it does not mention authentication or the shape of the success response, but this is minor for such a simple action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is 100% trivially. The description adds meaning about the action's purpose without needing to explain parameters, so the baseline 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Perform') and a clear resource ('the daily check-in') with a concrete outcome ('collect energy points'). It is unambiguous and distinct from all sibling tools, none of which perform a daily check-in.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent this action can be performed once per day and that repeated calls will return an 'already checked in' result. This is clear usage context, though it does not discuss alternatives because none are relevant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 reveals a nontrivial behavior: 'Logs in automatically if needed,' which is important for an agent to anticipate side effects. It also implies a read-only operation via 'Get,' though it does not explicitly rule out modifying state or describe login side-effect details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two tight sentences: the first front-loads the purpose and return contents, and the second adds the one essential behavioral caveat about automatic login. Every word earns its place with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless, read-style tool with no output schema, this description is complete: it names the target entity, the available data fields, and the login behavior an agent must know before calling. Nothing essential is missing for correct invocation or interpretation of results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the input schema already covers everything. The description appropriately adds no parameter documentation because none is needed, which matches the schema coverage of 100%. A baseline of 4 is appropriate for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'Get the currently logged-in NodeLoc user' and lists the exact returned fields (id, username, trust level, unread notification counts). This clearly distinguishes it from sibling tools like get_user_profile or get_user_summary, which target other users rather than the active session.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'currently logged-in NodeLoc user' provides clear context for when to call this tool: when the agent needs data about the authenticated user. The mention that it logs in automatically also signals that no separate authentication step is required. It does not explicitly name alternatives or exclusions, 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.

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