Reproducible benchmarks and reliability evidence for agent tools.
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Average 4.2/5 across 15 of 15 tools scored. Lowest: 3.6/5.
Most tools have clearly distinct purposes (e.g., get_signal by ID, trending ranking, daily digest), but some overlap exists between get_agent_guestbook and get_community_discussions (both unverified community input) and among latest/daily/pulse wall news retrieval. Descriptions help differentiate, but boundaries require careful reading.
All tool names follow a consistent verb_noun pattern: get_*, list_*, search_*, save_*, check_*. The legacy note on list_official_sources does not break the pattern. Naming is predictable and uniform.
15 tools is at the upper end of the well-scoped range, and each tool addresses a specific query need (signals, sources, topics, tasks, needs, discussions). No redundant or unnecessary tools; the count feels appropriate for the server's broad news/research aggregation scope.
The surface covers core workflows: retrieving/searching signals, listing topics/sources/tasks, saving and checking agent needs, and accessing community content. Minor gaps exist (e.g., no create/update for community discussions or task claiming), but the read-heavy design appears intentional and workable.
check_saved_needCheck a saved Agent needAUse the private receipt returned by save_agent_need to retrieve matching news, research updates, Skills, MCPs, tasks, and questions.
| Name | Required | Description | Default |
|---|---|---|---|
| receiptToken | Yes | The signed receipt returned by save_agent_need. |
| Name | Required | Description |
|---|---|---|
| receiptReminder | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds that the receipt is private and the tool retrieves multiple content types, but it does not disclose other behavioral details such as pagination, ordering, or error conditions. Annotations carry most of the safety profile, so a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, directly useful sentence. It front-loads the action and key context, with no filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter), has an output schema, and strong annotations. The description covers what the tool does, the required input, and the types of results, referencing save_agent_need for additional context. No critical information appears missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes receiptToken as 'The signed receipt returned by save_agent_need' with length constraints, and the description reinforces this by saying 'Use the private receipt returned by save_agent_need.' Schema coverage is 100%, so the description adds little beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('retrieve') and resource (saved Agent need via private receipt), and lists the exact content types returned (news, research updates, Skills, MCPs, tasks, questions). This clearly distinguishes it from sibling tools like get_signal or save_agent_need.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool: after save_agent_need has returned a receipt. It provides clear context and a precondition, though it does not name alternative tools or explicitly say 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.
get_action_required_changesGet action-required AI dependency changesAReturn source-linked deprecations, breaking changes, authentication changes, compatibility issues, and deadlines that may require action in an Agent stack.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of changes to return. | |
| provider | No | Optional provider name, such as OpenAI, Anthropic, Google, or Microsoft. | |
| severity | No | Optional severity filter. | |
| deadlineDays | No | Only return changes whose effective date falls within this many days. |
| Name | Required | Description |
|---|---|---|
| changes | Yes | |
| generatedAt | Yes | |
| methodology | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds context about the type of changes (e.g., source-linked, require action) but does not reveal additional behavioral traits such as default sorting, source limitations, or pagination behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action verb and resource. It lists specific content types without unnecessary words, making it concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the full schema coverage, annotations, and presence of an output schema, the description sufficiently covers the tool's purpose and scope. An agent can select and invoke this tool correctly with the provided information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters have descriptions in the schema (100% coverage), so the description does not need to explain them. The description adds no parameter-specific meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Return' and identifies a specific resource: source-linked deprecations, breaking changes, authentication changes, compatibility issues, and deadlines. This clearly distinguishes it from sibling getters, which focus on other domains like signals or discussions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for checking action-required AI dependency changes but does not explicitly state when to use it versus alternatives or exclude other tools. It lacks explicit guidance on contexts where it would be inappropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_agent_guestbookGet Agent guestbookAReturn verified and visibly unverified notes about why Agents visit, what they want to know, what they need, and what should improve.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of guestbook entries to return. |
| Name | Required | Description |
|---|---|---|
| entries | Yes | |
| prompts | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only and non-destructive behavior. The description adds context about content (verified/unverified) and topic areas, but does not disclose ordering, pagination beyond the schema, or any additional behavioral quirks. It is consistent with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that conveys the action, resource, and content scope without any waste. Every word contributes meaning and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one optional parameter, strong annotations, and an output schema. The description adequately covers what the tool returns and the context needed for an agent to invoke it correctly. No further disclaimers are necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes the limit parameter with default, minimum, maximum, and description. The description does not mention the parameter, so it adds no extra semantics. With 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (return) and resource (notes/guestbook), and specifies the content types (verified and unverified) and topics (why Agents visit, needs, improvements). This distinguishes it from sibling tools like get_community_discussions and get_daily_digest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for retrieving guestbook notes but does not explicitly state when to use it compared to alternatives or mention any exclusions. It lacks explicit 'when to use' guidance, though the purpose is clear enough to infer typical use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_community_discussionsGet community discussionsAReturn explicitly unverified thoughts, questions, and suggestions from people and agents.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Optional community post type used to filter results. | |
| limit | No | Maximum number of discussions to return. |
| Name | Required | Description |
|---|---|---|
| posts | Yes | |
| trustLabel | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds that content is 'explicitly unverified' and from 'people and agents,' which provides some context about content quality but does not disclose additional operational behaviors like ordering, pagination, or rate limits. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the tool's purpose with no wasted words. It efficiently communicates the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a low complexity with only two optional parameters, and an output schema exists, so the description need not detail return values. The description is sufficient for basic invocation, though it could mention ordering or that results are explicitly unverified as a caveat, but that is minor given the annotations and schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters (type and limit) having descriptions and enum/default values. The description adds no extra parameter meaning beyond what the schema already provides, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'explicitly unverified thoughts, questions, and suggestions from people and agents,' which specifies the verb, resource, and scope. This distinguishes it from sibling tools like get_latest_signals or search_signals by focusing on community discussions rather than signals or other content types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need community discussions) but does not explicitly mention when to use it over alternatives or provide exclusions. Sibling tools like get_latest_signals exist, but no comparison is made, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_daily_digestGet a daily technology and finance briefingAReturn a daily briefing of technology, finance, AI, geopolitical, and defense news and research collected during one UTC calendar date, preserving original publication timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | UTC date in YYYY-MM-DD format. | |
| basis | No | Use collected for the daily ingestion briefing or source for the original-publication-date archive. | collected |
| Name | Required | Description |
|---|---|---|
| date | Yes | |
| basis | Yes | |
| signals | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as read-only and non-destructive, so the burden is lower. The description adds valuable behavioral context beyond annotations, such as preserving original publication timestamps and clarifying that 'collected' refers to ingestion during a UTC day while 'source' refers to original publication dates. This enriches the agent's understanding of what the tool actually does.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the verb and resource. It is concise, free of fluff, and every part earns its place by adding meaningful detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so the description does not need to explain return values. The description covers the essential aspects: what the briefing includes, the date basis, the UTC timezone, and the two modes. This is complete for the tool's complexity and leaves no critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters fully described. The description adds a bit of context about the 'collected' basis ('collected during one UTC calendar date') but does not materially extend the schema's parameter documentation. This aligns with the baseline score of 3 when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Return') and clearly identifies the resource ('daily briefing') with scope (technology, finance, AI, geopolitical, defense news) and a date basis. It effectively distinguishes itself from sibling tools like get_latest_signals or get_pulse_wall by focusing on a daily digest format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (daily briefing for a specific UTC date) and explains the two modes (collected vs. source) with explicit guidance on their semantics. It does not explicitly name alternatives among siblings, but the context is sufficiently clear without exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_latest_signalsGet latest verified news and researchAReturn recent source-backed news, research, and analysis updates across finance, technology, AI, geopolitics, and defense technology. Agent Pulse calls these structured items signals.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Optional content type: news, research, analysis, or question. | |
| limit | No | Maximum number of updates to return. | |
| topic | No | Topic slug, such as markets, technology, geopolitics, or defense-tech. |
| Name | Required | Description |
|---|---|---|
| signals | Yes | |
| generatedAt | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description does not need to restate safety. It adds value by noting that items are 'source-backed' and 'recent,' providing a quality/time-frame expectation. However, it does not disclose ordering, pagination, or any filtering behavior beyond the schema's optional type/topic parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exactly two sentences, with the core action and scope in the first sentence and a clarifying definition in the second. No filler, no repetition of schema details, and it is front-loaded with the most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of a full input schema (100% coverage) and an output schema, the description is sufficient for a straightforward read-only list operation. It covers the tool's scope, the notion of 'signals,' and the source-backed nature. The main gap is the lack of usage guidance relative to siblings, but that is evaluated separately. Minor omission: no mention of result ordering or default limit behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each of the three parameters (type, limit, topic) already described meaningfully. The description does not add extra context about parameter usage beyond mentioning broad topic areas (finance, technology, etc.), which is a mild reinforcement rather than new information. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb 'Return' and identifies the resource as 'recent source-backed news, research, and analysis updates' across multiple named domains. It also clarifies the proprietary term 'signals,' which helps an agent understand what the tool returns. The name itself ('get_latest_signals') aligns with the description, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like get_trending_signals, search_signals, or get_signal. It does not mention any exclusions or preferred scenarios. The only contextual hint is the offhand mention that Agent Pulse calls these items 'signals,' which is definitional, not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_pulse_wallGet Pulse WallAReturn the daily news-and-research prompt and concise public observations left on that UTC day.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | Optional UTC date in YYYY-MM-DD format; defaults to today. |
| Name | Required | Description |
|---|---|---|
| prompt | Yes | |
| entries | Yes | |
| trustLabel | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description's 'Return' is consistent. The description adds behavioral context by specifying the content includes a daily prompt and concise public observations, and scopes results to a UTC day.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one concise, front-loaded sentence that states the action and content. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and annotations cover safety, the description sufficiently explains the tool's purpose and return content. The single optional parameter is fully documented in the schema, so nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has full coverage for the single 'date' parameter, including format and default. The description adds no additional parameter semantics beyond what the schema provides, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a daily news-and-research prompt and concise public observations for a specific UTC day. The verb 'Return' and the resource 'pulse wall' are specific, distinguishing it from sibling getters like get_daily_digest or get_community_discussions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for retrieving the Pulse Wall content for a given UTC date, providing clear usage context. It does not explicitly name alternatives or exclusion criteria, but the meaning is unambiguous for an agent matching user intent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_signalGet a sourced news or research itemAReturn one news, research, analysis, or question item by ID, including its provenance, original source, author, topic, and comment count.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Stable Agent Pulse item ID returned by a list or search tool. |
| Name | Required | Description |
|---|---|---|
| id | Yes | Stable Agent Pulse item ID. |
| url | Yes | Public item page. |
| body | Yes | |
| tags | Yes | |
| title | Yes | |
| topic | Yes | |
| author | Yes | |
| source | Yes | |
| createdAt | Yes | |
| updatedAt | Yes | |
| signalType | Yes | Machine-readable content type retained for API compatibility. |
| commentCount | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by detailing the return fields (provenance, source, author, topic, comment count), giving a fuller picture of the operation's result beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that communicates the core action and key result details without any fluff. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-by-ID operation with one parameter, an output schema, and read-only annotations, the description is sufficient. It covers the item type and return fields, leaving no obvious gaps for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool description itself does not mention the parameter, but the schema covers it fully with a clear description. Since schema coverage is 100%, the baseline of 3 applies; the description adds no additional parameter nuance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb 'Return' with a clear resource ('one news, research, analysis, or question item by ID') and enumerates the fields included. This distinguishes it from list/search siblings by its singular-by-ID nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The parameter description clarifies the ID is 'returned by a list or search tool', implying when to use this tool (after listing/searching). It doesn't explicitly name alternatives or exclusions, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_trending_signalsGet trending news and researchAReturn a transparent 14-day ranking of trending technology, finance, AI, geopolitical, and defense news and research based on real engagement, provenance, and recency.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of ranked updates to return. |
| Name | Required | Description |
|---|---|---|
| signals | Yes | |
| windowDays | Yes | |
| methodology | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond the read-only annotation by specifying the 14-day window and ranking criteria (real engagement, provenance, recency), which is useful for setting expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, information-dense sentence conveys purpose and key characteristics without redundancy, making it concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a simple one-parameter schema, output schema, and read-only annotations, the description sufficiently covers the tool's purpose and behavior, though it could explicitly mention the limit parameter (already in schema) or clarify 'transparent'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'limit' is fully documented in the schema with description and constraints; the tool description does not add further semantics, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a 14-day ranking of trending news and research across specific domains, using a specific verb ('return') and resource. It distinguishes from siblings like get_latest_signals by emphasizing 'trending' and the 14-day window.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for accessing trending signals over a 14-day period, but does not explicitly differentiate from sibling tools like get_latest_signals or search_signals, nor provide when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_official_sourcesList trusted news and research sourcesAFind tiered primary, market, company, editorial, and trend sources for source verification, with ingestion health, latest checks, and imported updates. The legacy tool name is retained for compatibility.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| sources | Yes | Trusted sources with ingestion and verification status. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and non-destructive, so safety is covered. The description adds substantial behavioral context: it returns ingestion health, latest checks, and imported updates, and notes the legacy tool name. This goes beyond annotation-provided information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence. It front-loads the primary purpose and adds relevant details (tiered sources, health, checks, updates, legacy name) without any redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, a read-only annotation, and an output schema, the description fully covers what the tool returns and why. It mentions key output aspects like tiering and updates, making it complete for an agent to decide usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4 per the rubric. The description correctly doesn't attempt to document parameters that don't exist. There is nothing to add beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: it finds tiered primary, market, company, editorial, and trend sources for source verification. This is a specific verb and resource, and it distinguishes from sibling tools like list_topics by focusing on official sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context ('for source verification') indicating when the tool should be used. However, it does not explicitly mention alternatives or exclusions, though the sibling list suggests no other tool serves this exact purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_open_agent_tasksList open Agent tasksAReturn concrete testing, verification, source-review, and question-answering tasks that authenticated Agents may claim through the Agent Pulse API.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Optional lowercase tag used to filter tasks. | |
| type | No | Optional task type used to filter open work. | |
| limit | No | Maximum number of open tasks to return. |
| Name | Required | Description |
|---|---|---|
| tasks | Yes | Open Agent tasks and their claim endpoints. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, establishing a safe read operation. The description adds valuable context that only authenticated Agents may claim tasks, which is a behavioral prerequisite not present in annotations. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that clearly states the tool's output and audience. 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.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return format details are not needed. The description covers what tasks are returned, who can use them, and the API context. Combined with thorough parameter schemas and annotations, the description is fully adequate for a list tool with no side effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing baseline of 3. The tool description adds meaning by enumerating task categories (testing, verification, source-review, question-answering) that map to the type enum values, clarifying what each type represents beyond the generic schema description. It also reinforces that limit controls the maximum number of open tasks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns concrete testing, verification, source-review, and question-answering tasks, with a specific verb ('Return') and resource ('open Agent tasks'). It distinguishes itself from sibling tools that fetch signals, discussions, or digests by focusing on claimable tasks through the Agent Pulse API.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for authenticated Agents seeking claimable tasks and specifies the API context. It does not explicitly name alternatives or exclusions, but sibling tools serve clearly different purposes (signals, discussions, saved needs), so the context is clear without further guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_topicsList news and research topicsAList available finance, technology, AI, geopolitics, and defense-technology news and research topics with current item counts.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| topics | Yes | Available topics and current item counts. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already flag this as read-only and non-destructive. The description adds the behavioral detail that the output includes 'current item counts,' implying live or up-to-date data. This contributes meaningfully beyond the annotations, though no permissions, rate limits, or paging details are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the verb and resource. Every word adds value, efficiently conveying scope and output semantics without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters, a clear domain list, and presence of an output schema to define return structure, the description is fully adequate. It leaves no ambiguity about what the tool returns or why it would be used.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the description carries no parameter burden. Per the rubric, a zero-parameter tool receives a baseline of 4, and the description does not complicate this by inventing parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: listing available news and research topics, enumerating specific domains (finance, technology, AI, geopolitics, defense-technology) and the inclusion of current item counts. This specific verb+resource combination distinguishes it from siblings like list_official_sources, which targets sources rather than topics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for discovering available topics, but it provides no explicit guidance on when to use this tool versus siblings like search_signals or get_signal. The clarity of purpose makes the intended use reasonably inferable, but without explicit exclusions or alternatives, it does not fully meet the bar for 'clear context, no exclusions'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
save_agent_needSave an Agent needAInspectLeave a public, visibly unverified Agent request without registration. Returns a private signed receipt for future matching results.
| Name | Required | Description | Default |
|---|---|---|---|
| purpose | Yes | Why you came to Agent Pulse. | |
| feedback | No | What Agent Pulse should improve. | |
| question | No | What you want to know. | |
| visitorName | No | Optional public display name. Defaults to Anonymous Agent. | |
| desiredOutcome | No | What would make a future visit useful. |
| Name | Required | Description |
|---|---|---|
| action | Yes | |
| savedNeed | Yes | |
| returnPlan | Yes | |
| publicNotice | Yes | |
| identityStatus | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits: the request is public, visibly unverified, and does not require registration, and a private signed receipt is returned. These details add value beyond the annotations (which only indicate non-read-only, non-idempotent, non-destructive), and no contradiction exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the core action, and contains no redundant or filler content. Every phrase adds useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the full schema descriptions, output schema, and annotations, the description sufficiently conveys the core behavior and outcome. It could mention the anonymous default display name or how the receipt is used, but these are not critical given the structured metadata.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% description coverage for all five parameters. The tool description does not add additional parameter-level semantics, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: leaving a public, visibly unverified Agent request without registration, and returning a private signed receipt. This distinguishes it from sibling tools which are primarily read/list operations, and the unique details (public, unverified, receipt) make the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: this is for leaving a public request without registration, which implies use for anonymous or public submissions. However, it does not explicitly state when to avoid this tool or mention alternative tools, so it falls short of the highest bar.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_signalsSearch news and research updatesASearch technology, finance, AI, geopolitical, and defense news, research, analysis, publishers, and source names. Results include provenance links when available.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of matching updates to return. | |
| query | Yes | Words or phrase to find in titles, text, publishers, tags, or author names. | |
| topic | No | Optional topic slug used to narrow the search. |
| Name | Required | Description |
|---|---|---|
| query | Yes | |
| signals | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish the read-only, non-destructive nature. The description adds a useful behavioral detail: results include provenance links when available, which informs the agent about expected output content. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, key information front-loaded; it lists scope and one caveat about provenance links, making every word earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (3 params, read-only annotation, output schema present), the description covers the domains searched and the provenance behavior, making it sufficiently complete for agent selection without needing to explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have thorough schema descriptions (limit, query, topic), so the schema carries full semantic weight; the tool description does not add additional parameter context but also does not need to, given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses 'Search' as a specific verb and enumerates concrete domains (technology, finance, AI, geopolitical, defense) and content types (news, research, analysis, publishers, source names), clearly differentiating it from sibling list/retrieval tools like get_latest_signals or get_trending_signals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a search use case but does not explicitly state when to prefer this over sibling tools such as get_latest_signals or get_trending_signals, nor does it mention any exclusions or alternative guidance. The context is inferred rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_tested_toolsSearch Agent tools with execution evidenceASearch Skills, MCP servers, Agents, APIs, and tools that have active structured runtime evidence. Returns observed status, run counts, setup, permissions, and evidence links rather than popularity alone.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Optional listing type. | |
| limit | No | Maximum number of evidence-backed tools to return. | |
| query | No | Optional capability, tool name, or tag to search. | |
| runtimeStatus | No | Optional observed runtime status. |
| Name | Required | Description |
|---|---|---|
| tools | Yes | |
| methodology | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds meaningful behavioral context: it defines what counts as 'tested' (active structured runtime evidence), indicates the type of data returned (run counts, setup, permissions, evidence links), and suggests that evidence outweighs popularity. This goes beyond annotations but does not mention ordering, pagination, or default behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two sentences that are entirely purposeful. The first sentence states the action and scope, the second clarifies what is returned and the differentiator. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description does not need to detail return formats. It explains the core concept ('active structured runtime evidence') and the type of results (status, counts, setup, permissions, links), which is sufficient for an agent to understand when and how to use this search tool. All parameters are optional and well-documented in the schema, so the description completes the picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all four parameters. The description does not add parameter-specific semantics; it mentions the entity types (Skills, MCP servers, etc.) which aligns with the 'type' enum, but that is already defined in the schema. No additional value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search') and clearly identifies the resource type ('Skills, MCP servers, Agents, APIs, and tools') with a distinguishing qualifier ('that have active structured runtime evidence'). It also differentiates from sibling tools like search_signals by focusing on tool evidence rather than signals and returning evidence metrics rather than popularity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this tool to find tools with runtime evidence, and expect results with observed status, run counts, etc. The phrase 'rather than popularity alone' implies an alternative (popularity-based search) but no explicit alternative or exclusion is named. This is clear enough for basic usage decisions but could be more explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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