exchange
Server Details
Exchange MCP — wraps the Frankfurter currency exchange API (free, no auth)
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-exchange
- GitHub Stars
- 0
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Usage analytics
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Tool Definition Quality
Average 3.8/5 across 9 of 9 tools scored. Lowest: 2.9/5.
Most tools have distinct purposes, such as convert for currency conversion, get_rate for current rates, and get_historical_rate for historical data. However, ask_pipeworx overlaps with discover_tools as both help find or use tools, which could cause confusion in selection.
The naming is mostly consistent with a verb_noun pattern, as seen in get_currencies, get_rate, and discover_tools. Minor deviations include ask_pipeworx (verb_proper_noun) and forget/recall/remember (single verbs without nouns), but overall it remains readable and predictable.
With 9 tools, the count is well-scoped for a server focused on currency exchange and tool discovery. Each tool serves a clear purpose, such as conversion, rate retrieval, memory management, and tool search, making the set appropriately sized without being overwhelming.
For currency exchange, the server covers core operations like conversion, current rates, historical rates, and currency listing. Minor gaps include lack of bulk conversions or rate alerts, but agents can work around this. The addition of memory and tool discovery tools adds utility beyond just exchange.
Available Tools
9 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that Pipeworx 'picks the right tool, fills the arguments, and returns the result,' which covers the automation aspect. However, it lacks details on limitations (e.g., data source availability, response time, error handling) or authentication needs, leaving gaps for a tool with such broad functionality.
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 front-loaded with the core functionality, uses efficient sentences, and includes relevant examples without redundancy. Every sentence adds value: the first explains the tool's purpose, the second details its automation, and the third provides concrete usage 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?
Given the tool's complexity (natural language querying with automated tool selection) and lack of annotations or output schema, the description does well by explaining the process and providing examples. However, it could be more complete by mentioning potential limitations or the types of data sources available, which would help set accurate expectations.
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 already documents the single 'question' parameter. The description adds value by emphasizing 'plain English' and 'natural language,' providing examples that illustrate the expected format beyond the schema's basic description. However, it doesn't detail constraints like length or supported topics.
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 purpose: 'Ask a question in plain English and get an answer from the best available data source.' It specifies the verb ('ask'), resource ('answer'), and mechanism ('Pipeworx picks the right tool, fills the arguments'), distinguishing it from sibling tools like currency converters or memory 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?
The description explicitly states when to use this tool: 'No need to browse tools or learn schemas — just describe what you need.' It provides clear alternatives (implicitly suggesting other tools for structured queries) and includes examples like 'What is the US trade deficit with China?' to illustrate appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convertCInspect
Convert an amount from one currency to another at current rates. Returns the converted amount and the exchange rate applied.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target currency code (e.g., JPY) | |
| from | Yes | Source currency code (e.g., USD) | |
| amount | Yes | Amount to convert |
Tool Definition Quality
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 mentions 'current exchange rate' but doesn't specify source, update frequency, or accuracy. It lacks details on error handling, rate limits, authentication needs, or what happens with invalid inputs. For a financial tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function. It's front-loaded with the core purpose and contains no unnecessary information. Every word earns its place, making it highly 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 tool's complexity (financial conversion with real-time data implications), no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error cases, or behavioral nuances like rate freshness. For a tool with these characteristics, more context is needed to be fully helpful to an AI agent.
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 description implies parameters (from, to, amount) but doesn't add meaning beyond what the input schema provides. With 100% schema description coverage, the schema already documents all three parameters clearly. The description doesn't provide additional context like currency code formats or amount constraints, so it meets the baseline for 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 clearly states the tool's purpose: converting an amount between currencies at current exchange rates. It specifies the verb ('convert') and resources ('amount from one currency to another'), but doesn't explicitly distinguish it from sibling tools like get_rate or get_historical_rate, which are related but serve different purposes.
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. It doesn't mention sibling tools like get_currencies, get_historical_rate, or get_rate, nor does it specify scenarios where this conversion tool is preferred over those alternatives. There's no context about prerequisites or limitations.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the search functionality and return format (tools with names/descriptions), but lacks details about performance characteristics (e.g., response time, rate limits), error conditions, or authentication requirements that would be helpful for an agent.
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 perfectly concise with two sentences that each serve distinct purposes: the first explains the core functionality, the second provides critical usage guidance. Every word earns its place with zero redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no annotations and no output schema, the description provides good context about when to use it and what it returns. However, it could be more complete by mentioning what happens when no tools match the query or providing more detail about the return format beyond 'names and descriptions.'
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 has 100% description coverage, so parameters are well-documented in the structured schema. The description doesn't add significant semantic context beyond what's already in the schema descriptions, maintaining the baseline score for 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 clearly states the tool's purpose with specific verbs ('search the Pipeworx tool catalog') and resource ('returns the most relevant tools with names and descriptions'). It distinguishes itself from sibling tools like currency converters by focusing on tool discovery rather than data retrieval or conversion operations.
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 guidance on when to use this tool ('call this FIRST when you have 500+ tools available and need to find the right ones for your task'). It also implicitly suggests alternatives (directly using known tools) by emphasizing this as an initial discovery step for large tool catalogs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetBInspect
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 provided, the description carries the full burden of behavioral disclosure. It states the tool deletes a memory, implying a destructive mutation, but doesn't cover critical aspects like whether deletion is permanent, requires specific permissions, has side effects, or provides confirmation. This leaves significant gaps 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It front-loads the core action ('Delete') and resource, making it immediately understandable. Every word earns its place, achieving optimal conciseness.
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 destructive tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., permanence, error handling), usage context, and return values. While concise, it doesn't provide enough information for safe and effective use in a complex system.
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 description adds minimal value beyond the input schema, which has 100% coverage and documents the 'key' parameter adequately. The description mentions 'by key' but doesn't elaborate on key format, examples, or constraints. Given the high schema coverage, 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 specific action ('Delete') and resource ('a stored memory by key'), distinguishing it from sibling tools like 'recall' (retrieve) and 'remember' (store). It uses precise language that leaves no ambiguity about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., that a memory must exist to be deleted), exclusions, or comparisons to siblings like 'recall' (for retrieval) or 'remember' (for storage). Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_currenciesAInspect
List all supported currencies with codes and full names. Use to verify currency codes before converting or checking rates.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
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 describes the action as a list operation, implying read-only behavior, and specifies the data source (Frankfurter API) and output detail ('full names'). However, it does not mention potential limitations like rate limits, error handling, or response format beyond the names.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('List all currencies') and includes essential details (API source and output format) without any wasted words. Every element serves a clear 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?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is complete enough for a simple list operation. It specifies the API source and output detail, though it could benefit from mentioning the response structure or any constraints to achieve full completeness.
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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately adds value by explaining the tool's purpose and output without redundant parameter details, earning a baseline score of 4 for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('List all currencies') and resource ('supported by the Frankfurter API'), distinguishing it from sibling tools like convert, get_historical_rate, and get_rate. It explicitly mentions 'with their full names' to specify the output scope.
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 by specifying 'supported by the Frankfurter API' and the output format, but does not explicitly state when to use this tool versus alternatives like get_rate or get_historical_rate. It provides clear context but lacks explicit exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_historical_rateBInspect
Get the exchange rate between two currencies on a specific date (format: YYYY-MM-DD). Returns the historical rate and date.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target currency code (e.g., EUR) | |
| date | Yes | Date in YYYY-MM-DD format (earliest available: 1999-01-04) | |
| from | Yes | Source currency code (e.g., USD) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the basic operation but lacks behavioral details like rate limits, authentication needs, error conditions (e.g., invalid dates or currencies), data source, or return format. The description doesn't contradict annotations (none exist).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose with no wasted words. Every element ('Get', 'exchange rate', 'two currencies', 'specific historical date', 'YYYY-MM-DD') contributes directly to understanding the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool with 3 parameters. It covers the basic operation but lacks critical context like return value structure, error handling, data freshness, or limitations (e.g., date range constraints beyond the schema's 'earliest available' note).
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 clear parameter documentation. The description adds minimal value beyond the schema by reinforcing the date format (YYYY-MM-DD) and historical context, but doesn't explain parameter interactions or provide additional semantics like currency code examples beyond what's in 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 specific action ('Get the exchange rate') and resource ('between two currencies on a specific historical date'), using a precise verb. It distinguishes from sibling tools like 'get_rate' (likely current rate) and 'convert' (likely conversion operation) by specifying the historical aspect.
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 ('on a specific historical date') but doesn't explicitly state when to use this tool versus alternatives like 'get_rate' (presumably for current rates) or 'convert' (presumably for actual conversions). No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_rateBInspect
Get the current exchange rate between two currencies (e.g., USD, EUR). Returns the rate value and timestamp.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target currency code (e.g., EUR, JPY, CHF) | |
| from | Yes | Source currency code (e.g., USD, EUR, GBP) |
Tool Definition Quality
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 the tool retrieves current exchange rates but lacks details on data sources, accuracy, rate limits, error handling, or response format. This is a significant gap for a tool that likely relies on external APIs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose with an illustrative example. There's zero waste, and it's appropriately sized for a simple tool with two parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple but with potential external dependencies), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like rate limits, data freshness, or error cases, which are critical for an exchange rate tool. More context is needed for reliable 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?
Schema description coverage is 100%, with clear parameter descriptions in the schema. The description adds minimal value beyond the schema by providing an example (e.g., USD to EUR) but doesn't explain parameter constraints or usage beyond what's already documented. Baseline 3 is appropriate given 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 clearly states the tool's purpose with a specific verb ('Get') and resource ('exchange rate between two currencies'), including an example. It distinguishes from sibling tools by focusing on current rates rather than conversion, historical data, or currency lists, though it doesn't explicitly name alternatives.
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?
Usage is implied through the description's focus on 'current exchange rate,' suggesting this tool is for real-time rates rather than historical data (get_historical_rate) or currency conversion (convert). However, there's no explicit guidance on when to use this versus siblings or any prerequisites.
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 are provided, so the description carries the full burden. It discloses that memories can be retrieved from 'earlier in the session or in previous sessions', indicating persistence across sessions. However, it doesn't mention error handling (e.g., what happens if key doesn't exist), performance characteristics, or authentication needs, leaving 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences that are front-loaded: the first sentence states the core functionality, and the second provides additional context. Every sentence earns its place by adding clear value 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?
Given the tool's moderate complexity (one optional parameter) and no output schema, the description is mostly complete. It explains what the tool does, when to use it, and the parameter's effect. However, it lacks details on return format (e.g., structure of retrieved memories or list) and error cases, which could be important for an agent.
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 already documents the single parameter 'key'. The description adds value by explaining the semantic effect of omitting the key ('omit to list all keys') and connecting it to retrieving 'context you saved earlier', which provides context beyond the schema's technical specification.
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 purpose with specific verbs ('retrieve', 'list') and resources ('previously stored memory', 'all stored memories'). It distinguishes from siblings by mentioning 'context you saved earlier' which implies it complements 'remember' and contrasts with 'forget'.
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 guidance on when to use this tool vs alternatives: 'Retrieve a previously stored memory by key, or list all stored memories (omit key)' gives clear conditional usage. It also mentions 'Use this to retrieve context you saved earlier in the session or in previous sessions' which distinguishes it from tools like 'get_rate' or 'convert'.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: it stores data in session memory, specifies persistence differences for authenticated vs. anonymous users (persistent vs. 24-hour lifespan), and implies it's a write operation. However, it lacks details on potential limitations like storage capacity, error conditions, or how it interacts with other memory tools.
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 front-loaded with the core purpose in the first sentence, followed by usage context and behavioral details. Both sentences earn their place by adding essential information without redundancy, making it efficient and well-structured for quick understanding.
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's moderate complexity (a write operation with no annotations and no output schema), the description is largely complete: it covers purpose, usage, and key behavioral aspects like persistence. However, it lacks details on return values or error handling, which would be beneficial since there's no output schema, leaving a minor gap in full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with both parameters ('key' and 'value') well-documented in the schema. The description does not add significant meaning beyond the schema (e.g., it doesn't explain parameter constraints or usage nuances), so it meets the baseline of 3 for high schema coverage without extra value.
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 specific action ('Store a key-value pair') and resource ('in your session memory'), distinguishing it from sibling tools like 'forget' (likely for deletion) and 'recall' (likely for retrieval). It specifies the purpose as saving intermediate findings, user preferences, or context across tool calls, making it distinct and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool ('to save intermediate findings, user preferences, or context across tool calls'), but it does not explicitly state when not to use it or name alternatives (e.g., compared to 'recall' for retrieval). The guidance is helpful but lacks explicit exclusions or sibling tool comparisons.
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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