Google_ads
Server Details
Google Ads MCP Pack
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-google_ads
- GitHub Stars
- 0
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Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
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Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.8/5 across 10 of 10 tools scored. Lowest: 3.2/5.
The set mixes general-purpose memory tools (forget, recall, remember) and Google Ads tools, plus two Pipeworx meta-tools. The Google Ads tools are distinct, but ask_pipeworx overlaps conceptually with the dedicated gads_* tools since it can also answer ad queries, creating ambiguity.
Most Google Ads tools follow a consistent 'gads_verb_noun' pattern. However, the meta-tools (ask_pipeworx, discover_tools) and memory tools (remember, recall, forget) use different conventions, breaking full consistency.
With 10 tools, the count is well-scoped. The Google Ads domain has 5 focused tools, complemented by 2 Pipeworx tools and 3 memory tools, each earning its place without being overwhelming.
The Google Ads tools cover listing campaigns and ad groups, getting campaign details, and fetching metrics, but lack create/update/delete operations. The advanced GAQL query tool partially fills gaps, but CRUD operations are missing, leaving notable gaps for lifecycle management.
Available Tools
10 toolsask_pipeworxAInspect
Ask a question in plain English and get an answer from the best available data source. Pipeworx picks the right tool, fills the arguments, and returns the result. No need to browse tools or learn schemas — just describe what you need. Examples: "What is the US trade deficit with China?", "Look up adverse events for ozempic", "Get Apple's latest 10-K filing".
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Your question or request in natural language |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It explains that Pipeworx selects the right tool and fills arguments, but does not disclose any limitations, required permissions, or whether the tool is read-only or destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences with front-loaded purpose. Every sentence adds value: defines the tool, explains automation, and gives concrete examples.
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 single-parameter tool with no output schema, the description is largely complete. It explains how the tool works and what to expect, though it could mention whether answers are textual or structured.
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 a single parameter 'question' described as 'Your question or request in natural language'. The description adds value by explaining the parameter's role and providing examples, exceeding the schema alone.
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 accepts plain English questions and returns answers from the best available data source. It provides specific examples, 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 explains when to use the tool (for natural language questions) and implies not needing to browse other tools. However, it does not explicitly state when not to use it or provide alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
discover_toolsAInspect
Search the Pipeworx tool catalog by describing what you need. Returns the most relevant tools with names and descriptions. Call this FIRST when you have 500+ tools available and need to find the right ones for your task.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of tools to return (default 20, max 50) | |
| query | Yes | Natural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries") |
Tool Definition Quality
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 states that the tool searches and returns tools with names and descriptions, which is clear. However, it does not disclose any behavioral traits like whether the search is case-sensitive, how the ranking works, or any side effects. The description is adequate but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, each serving a clear purpose: stating the action and providing usage guidance. No wasted words, and the key information is front-loaded. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has only 2 parameters (both documented), no output schema, and the context signals indicate low complexity, the description provides enough information for an agent to use it effectively. The only minor gap is the lack of detail on how results are ranked, but for a discovery tool, this is acceptable.
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 baseline is 3. The description does not add any additional meaning beyond what the schema already provides for the 'query' and 'limit' parameters. It does provide a good example for the query parameter in the schema, but the description itself adds no extra context.
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 it searches the Pipeworx tool catalog by describing what you need, and returns the most relevant tools with names and descriptions. It explicitly calls out the use case: call this FIRST when you have 500+ tools available. This distinguishes it from other tools, 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 explicit usage guidance: 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This tells the agent when to use this tool (first step in tool discovery) and implies that other tools should be used for actual operations once the right tool is found.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetAInspect
Delete a stored memory by key.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key to delete |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. It correctly identifies the tool as destructive (delete), but lacks details on whether deletion is permanent, if confirmation is needed, or if related data is affected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys all essential information with no fluff. It is front-loaded and efficient.
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 simple tool (one param, no output schema, no nested objects), the description is adequate but could mention whether deletion is reversible or if there are any 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 coverage is 100% with one required 'key' parameter. The description adds clarity by specifying 'Memory key to delete', which reinforces the schema's purpose.
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 ('Delete'), the resource ('a stored memory'), and the parameter ('by key'). It is specific and distinct from sibling tools like 'recall' and 'remember'.
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 when you need to delete a memory, but does not provide guidance on when to use this tool versus alternatives like 'recall' or 'remember', nor does it mention prerequisites or consequences.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gads_campaign_metricsAInspect
Get performance metrics for campaigns over a date range. Returns impressions, clicks, cost, conversions, CTR, and CPC. Use to analyze campaign effectiveness or compare performance trends.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of rows to return (default 50) | |
| end_date | Yes | End date in YYYY-MM-DD format (e.g., "2024-01-31") | |
| start_date | Yes | Start date in YYYY-MM-DD format (e.g., "2024-01-01") | |
| campaign_id | No | Campaign ID to filter (optional, returns all campaigns if omitted) | |
| customer_id | Yes | Google Ads customer ID |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It correctly indicates it's a read operation returning metrics. However, does not disclose if there are rate limits, data latency, or whether it returns only active campaigns or all campaigns. Behavior is generally clear but lacks depth.
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?
Extremely concise: two sentences front-load the purpose and list metrics. No wasted words. Essential information presented efficiently.
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 no output schema and no annotations, the description is fairly complete for a simple metrics tool. However, it lacks details on pagination (limit parameter mentioned only in schema), data aggregation (daily or cumulative?), and whether campaigns without data are returned. Slight 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 already describes all parameters with full coverage. Description adds context by naming the returned metrics (impressions, clicks, etc.), which helps infer parameter usage but doesn't add significant meaning beyond the schema. 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?
Description clearly states it retrieves performance metrics for campaigns, listing specific metrics (impressions, clicks, cost, etc.). Distinguishes from siblings: 'gads_list_campaigns' likely lists campaigns without metrics, 'gads_get_campaign' is singular, but this one focuses on metrics.
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?
Description implies usage for retrieving campaign metrics over a date range. No explicit guidance on when to use this vs. other tools like 'gads_search' (which may provide more flexible queries). No mention of prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gads_get_campaignAInspect
Get detailed settings for a specific campaign. Returns name, status, budget, bidding strategy, and configuration. Use to review or audit a campaign's current setup.
| Name | Required | Description | Default |
|---|---|---|---|
| campaign_id | Yes | The campaign resource ID | |
| customer_id | Yes | Google Ads customer ID |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes the operation as a read ('Get') and lists returned fields, but doesn't disclose any side effects, permissions, or limitations. The description is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with no wasted words. Front-loaded with purpose and lists key return fields efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with two parameters and no output schema, the description is fairly complete. However, it could mention that it returns a single campaign object or any error conditions. Sibling tools provide context, but description alone is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds minimal value beyond field names. It implies customer_id and campaign_id are used to identify the campaign, which is obvious from the schema. No additional constraints or usage notes provided.
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 ('Get') and resource ('Google Ads campaign'), explicitly listing returned fields (name, status, budget, bidding strategy, settings) and distinguishing from siblings like gads_list_campaigns which lists campaigns.
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 clearly states the tool retrieves detailed info for a specific campaign, implying use when you have an ID. It doesn't explicitly mention when not to use it or alternatives, but context from siblings suggests gads_list_campaigns for listing, so guidance is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gads_list_ad_groupsBInspect
List ad groups within a campaign by campaign ID. Returns ad group names, IDs, statuses, and CPC bids. Use to explore campaign structure or select an ad group for analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of ad groups to return (default 50) | |
| status | No | Filter by ad group status (optional) | |
| campaign_id | Yes | Campaign ID to list ad groups for | |
| customer_id | Yes | Google Ads customer ID |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so description carries full burden. It discloses that the tool returns specific fields and supports filtering by status and limit, which is useful. However, it doesn't mention pagination, rate limits, or whether it only returns active ad groups by default.
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?
Description is concise (two sentences) and front-loads the purpose. No unnecessary words. However, it could mention the limit default and output fields more efficiently.
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 no output schema, the description adequately states what fields are returned. However, it lacks context on error handling, performance implications of listing many ad groups, or how to interpret the response structure. Could be more complete for a list operation.
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% and all parameters have descriptions, so baseline is 3. The description adds no extra meaning beyond what the schema already provides (e.g., doesn't clarify that 'status' filter defaults to all).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists ad groups for a campaign and specifies returned fields (names, IDs, statuses, CPC bid). However, it doesn't differentiate from sibling tools like gads_search or gads_list_campaigns, which could also list ad groups but with different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this vs. alternatives like gads_search, which might offer more flexible filtering. The description implies use for a specific campaign but doesn't mention prerequisites (e.g., campaign must exist) or 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.
gads_list_campaignsAInspect
List all campaigns in your Google Ads account. Returns campaign names, IDs, statuses, budgets, and types. Use to overview account structure or find a campaign ID for detailed analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of campaigns to return (default 50) | |
| status | No | Filter by campaign status (optional, returns all if omitted) | |
| customer_id | Yes | Google Ads customer ID (e.g., "1234567890" or "123-456-7890") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It states that it returns campaigns and lists fields, but does not disclose side effects (none expected, but not stated), performance limits, or whether it returns all campaigns or paginated results. Adequate but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and no wasted words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (no output schema, no nested objects), the description is adequate but could mention that results are paginated if limit is unspecified, or that all statuses are returned by default. It covers the basics but lacks some edge-case 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%, so the description adds minimal extra meaning beyond what the schema already provides. It mentions the returned fields but does not elaborate on parameter usage beyond listing them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'campaigns in a Google Ads account', and specifies the returned fields: names, IDs, statuses, budgets, and types. This differentiates it from siblings like gads_get_campaign (single campaign) and gads_campaign_metrics (metrics).
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 listing campaigns, but does not explicitly state when to use this tool over siblings like gads_search or gads_campaign_metrics. No exclusions or alternatives are mentioned, relying on the user to infer from tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gads_searchAInspect
Run custom GAQL queries against Google Ads data. Use for advanced analysis—filter by keywords, matching types, or aggregate metrics by custom dimensions.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | GAQL query string (e.g., "SELECT campaign.name, metrics.clicks FROM campaign WHERE segments.date DURING LAST_7_DAYS") | |
| customer_id | Yes | Google Ads customer ID |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries burden. It notes execution of arbitrary queries, implying flexibility but also risk. Lacks details on mutability, permissions, or rate limits. Adequate but not thorough.
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 short sentences with a link, no fluff. Front-loaded with purpose and use case.
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 no output schema, description is sufficient for a query execution tool. Could mention that output format is raw GAQL response, but otherwise complete.
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%, and description adds minimal extra meaning beyond schema. The GAQL syntax link provides value, but parameters are well-documented in 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?
Clearly states it executes a custom GAQL query, distinguishes from other tools by noting 'advanced queries not covered by other tools'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use when other tools don't cover the query, and provides a link to GAQL syntax. Could mention when not to use, but context implies it's for complex cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recallAInspect
Retrieve a previously stored memory by key, or list all stored memories (omit key). Use this to retrieve context you saved earlier in the session or in previous sessions.
| Name | Required | Description | Default |
|---|---|---|---|
| key | No | Memory key to retrieve (omit to list all keys) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It explains the key behavior (omit to list) and purpose (retrieve saved context). However, it doesn't disclose side effects, return format, or error cases, which would be helpful.
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, both essential. No fluff. First sentence states action, second sentence explains purpose.
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?
Tool is simple (0 required params, no output schema). Description explains both modes (retrieve by key, list all) and rationale. No output schema needed for a retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'key'. Description adds context by explaining that omitting key lists all memories, which complements the schema's description. 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?
Description clearly states the tool retrieves a memory by key or lists all memories when key is omitted. It distinguishes from sibling tools like 'remember' (store) and 'forget' (delete), but doesn't explicitly name them.
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?
Explicitly says when to use: to retrieve context saved earlier. Implicitly contrasts with 'remember' (store) and 'forget' (delete). No explicit when-not-to-use or alternatives listed, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rememberAInspect
Store a key-value pair in your session memory. Use this to save intermediate findings, user preferences, or context across tool calls. Authenticated users get persistent memory; anonymous sessions last 24 hours.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key (e.g., "subject_property", "target_ticker", "user_preference") | |
| value | Yes | Value to store (any text — findings, addresses, preferences, notes) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses persistence behavior (authenticated vs anonymous sessions) and implicit state modification. With no annotations provided, description carries full burden; it adds behavioral context about session duration but lacks details on overwrite behavior or limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with action, usage guidance, and behavioral note. Every sentence adds value; 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 no output schema and no annotations, description covers purpose, usage, and persistence. Could mention overwrite behavior or key uniqueness, but overall sufficient for a simple key-value store.
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 baseline is 3. Description adds minimal extra meaning beyond schema; schema already provides clear examples for 'key' and type for 'value'. No additional parameter context in description.
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?
Clearly states verb 'store' and resource 'key-value pair in your session memory', and distinguishes from sibling 'recall' by focusing on storage vs retrieval. No ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'use this to save intermediate findings, user preferences, or context across tool calls', providing clear when-to-use guidance. Does not explicitly mention when not to use or alternatives, but context is strong.
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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