Hud
Server Details
HUD MCP — U.S. Department of Housing and Urban Development APIs.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-hud
- GitHub Stars
- 0
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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 4/5 across 10 of 10 tools scored. Lowest: 3.4/5.
Most tools are clearly distinct: HUD tools (chas, crosswalk, fmr, income_limits, list_states) serve different housing data needs, and memory tools (forget, recall, remember) are separate. However, ask_pipeworx overlaps with discover_tools in that both help find data, though ask_pipeworx directly answers while discover_tools returns tool names.
Tool names are mostly descriptive and use underscore separation, but there is inconsistency: some start with 'hud_' for domain-specific tools, while memory tools use generic verbs (forget, recall, remember). ask_pipeworx and discover_tools break the pattern by not following a verb_noun structure.
With 10 tools, the count is well-scoped for a server providing HUD data access and memory management. Each tool serves a clear purpose without redundancy, and the number is appropriate for the domain.
The HUD data tools cover key datasets (CHAS, crosswalk, FMR, income limits, states), but there are obvious gaps: no tools for updating or deleting data (HUD API is read-only), and missing common HUD data like public housing agency info. The memory tools provide basic CRUD but lack search or batch operations.
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?
The description discloses that the tool internally selects the right tool and fills arguments, abstracting complexity. No annotations are provided, so the description carries full burden. It clearly states behavior: it returns an answer from the best data source without needing to browse tools or schemas.
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, with three sentences plus examples. It front-loads the core purpose and provides useful examples. No unnecessary words, though the examples could be more 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 single parameter and no output schema, the description adequately covers its purpose and behavior. It explains what the tool does internally (routing) and provides examples. For a tool of this complexity, the description is nearly complete; it could mention limitations (e.g., scope of data sources) but is sufficient.
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 value by explaining the question parameter as 'your question or request in natural language,' which aligns with the schema description. With 100% schema description coverage, the baseline is 3. The description does not add further detail beyond examples, but the examples enrich the semantic understanding.
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 natural language questions and returns answers, using the best available data source. It distinguishes itself from sibling tools by acting as an intelligent router, unlike specific data lookup tools (e.g., hud_fair_market_rents). Examples make the purpose concrete.
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 advises users to 'just describe what you need' and provides example questions, implying when to use this tool (for any data question in plain English). It does not explicitly state when not to use it or mention alternatives, but the context suggests this is the go-to tool for natural language queries.
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?
The description explains that it returns the most relevant tools with names and descriptions, which is a clear behavioral trait. No annotations are provided, so the description carries the full burden. It could add detail about whether the search is semantic or keyword-based, but it is sufficiently transparent for a search 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 three sentences, all front-loaded with the action verb 'Search'. Every sentence adds value: purpose, output, and when to use. No waste.
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 simplicity (search, two params, no output schema), the description is complete enough. It explains what the tool does and when to use it. Could mention that it returns results with names and descriptions, which it does. No output schema, so return values are not documented but are implied.
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 high coverage (100%) with descriptions for both parameters. The description adds context that 'query' should be a natural language description, reinforcing the schema's description. It does not add new semantics beyond the schema, but it aligns well.
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: to search the tool catalog by describing what you need, returning relevant tools with names and descriptions. It uses specific verbs ('search', 'call this first') and distinguishes itself from siblings by being a discovery tool for finding 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?
The description explicitly tells when to use it: 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This provides clear guidance and context for when it should be invoked, setting it apart from other tools.
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?
The description indicates a destructive action (delete), which is clear. No annotations provided, so the description carries the full burden. It states the operation is irreversible (delete), which is good, but no additional context like whether confirmation is needed or if it's permanent.
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 extremely concise with one short sentence. Every word is necessary, and it's front-loaded with the action and object.
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 delete operation with one parameter and no output schema, the description is nearly complete. It lacks information about return value or confirmation, but for such a simple tool, it's 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?
The schema description coverage is 100% for the single required parameter 'key'. The description adds meaning by specifying it's a 'memory key', which aligns with the schema description. No extra semantic info beyond the schema, but given high coverage, a 4 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 uses a specific verb ('Delete') and resource ('stored memory by key'). It clearly states what the tool does. However, it could be more distinctive from siblings like 'recall' or '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 want to delete a memory by key, but no guidance on when not to use it or alternatives. Given the sibling tools, there's no explicit mention of 'forget' vs 'recall' or 'remember'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hud_chasAInspect
Get housing affordability data by income level and family type. Returns household counts with cost burdens, overcrowding, and housing problems. Use for housing needs assessment.
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Data year (e.g., 2020). Omit for the most recent available. | |
| _apiKey | Yes | HUD API token | |
| entity_id | No | FIPS code for a specific county or place. Omit to get state-level data. | |
| state_code | Yes | Two-letter state code (e.g., "CA", "NY"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so the description must disclose behavioral traits. It notes that data is from HUD and focuses on low-income households, but does not mention data limitations, update frequency, or any constraints like rate limits or authentication requirements (beyond the API key parameter).
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 three sentences, front-loaded with the core action and followed by purpose and usage context. No fluff 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?
Given the tool has no output schema, the description could be more specific about the return format or data structure, but it provides enough context for the agent to understand the tool's purpose and typical use. The input schema is comprehensive, so the description 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 schema already documents all parameters. The description adds context about the data's purpose but does not add semantics beyond the schema for individual parameters. 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 clearly states it gets CHAS data from HUD and explains its purpose (demonstrating housing problems and needs, used for planning affordable housing). The verb 'Get' combined with the resource 'Comprehensive Housing Affordability Strategy (CHAS) data' is specific and distinct from sibling tools like hud_fair_market_rents or hud_income_limits.
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 cases for planning affordable housing, but does not explicitly state when not to use it or suggest alternatives among sibling tools. However, the context of 'communities to plan affordable housing' provides clear usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hud_crosswalkBInspect
Map ZIP codes to census tracts, counties, CBSAs, and congressional districts. Returns geographic identifiers. Use to translate between location code formats or join datasets.
| Name | Required | Description | Default |
|---|---|---|---|
| type | Yes | Crosswalk type: 1=ZIP-to-tract, 2=ZIP-to-county, 3=ZIP-to-CBSA, 4=ZIP-to-congressional-district, 7=county-to-ZIP. | |
| query | Yes | Input value: ZIP code (for types 1-4), or FIPS county code (for type 7). Example: "90210" or "06037". | |
| _apiKey | Yes | HUD API token |
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 states the tool 'maps' and is 'essential for geographic analysis', which suggests a read-only operation. However, it does not disclose details like API rate limits, authentication needs (only mentions an API key parameter but not required permissions), or whether the crosswalk data is updated periodically. Adequate but minimal behavioral context.
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 waste. First sentence defines the tool, second sentence gives usage context. Efficient 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?
Given 3 simple parameters, 100% schema coverage, no output schema, and no annotations, the description is fairly complete. It explains what the tool does and why it's useful. Could mention that results are typically a list of geographic codes, but not essential.
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%, and the description adds value by explaining the mapping types (e.g., ZIP-to-tract) and providing examples like '90210' and '06037'. This goes beyond the schema's basic parameter descriptions.
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 that the tool maps between ZIP codes, census tracts, counties, CBSAs, and congressional districts, using a specific verb 'Maps' and resource 'HUD USPS ZIP code crosswalk'. It distinguishes from siblings like hud_chas or hud_fair_market_rents by focusing on geographic crosswalking, but could be more explicit about its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description implies it's for geographic analysis when joining data from different sources, but does not specify when not to use it or mention sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hud_fair_market_rentsAInspect
Get Fair Market Rent ceilings by bedroom count (0–4+) for a specific area and year. Returns rent limits by bedroom count. Use to set voucher payment standards and rental assistance caps.
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Fiscal year (e.g., 2024). Omit for the most recent year. | |
| _apiKey | Yes | HUD API token | |
| entity_id | No | FIPS code or ZIP code to get FMR for a specific area. Omit to get all areas in the state. | |
| state_code | Yes | Two-letter state code (e.g., "CA", "NY", "TX"). Required to get state-level summary. |
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 what FMRs are used for but does not disclose any side effects, rate limits, or authentication requirements beyond the API key parameter.
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 with three sentences: purpose, context, output. No redundancy, front-loaded with key action.
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 explains return value (rent estimates by bedroom count). Complexity is moderate, and description covers core functionality adequately.
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 baseline is 3. Description does not add meaning beyond schema; it mentions 'by bedroom count' but that is implicit in output, not 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 retrieves Fair Market Rents from HUD and explains their use cases (Housing Choice Voucher, Section 8, HOME). It distinguishes from siblings like hud_income_limits and hud_chas by focusing on rent estimates by bedroom count.
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 obtaining FMR data but lacks explicit guidance on when to use this vs. other HUD tools. No mention of prerequisites (e.g., API key) or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hud_income_limitsAInspect
Check income eligibility thresholds (extremely low, very low, low-income) for HUD programs by area and family size. Returns income limits by category. Use to determine program qualification.
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Fiscal year (e.g., 2024). Omit for the most recent year. | |
| _apiKey | Yes | HUD API token | |
| entity_id | No | FIPS code or metro area code for a specific area. Omit to get all areas in the state. | |
| state_code | Yes | Two-letter state code (e.g., "CA", "NY"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Describes return thresholds but does not disclose pagination, rate limits, or whether the API requires authentication beyond the API key. Does not mention if data is cached or real-time.
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 concise sentences that front-load the purpose. No wasted words, but could be slightly more structured with bullet points for the return values.
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 explains the return thresholds. Tool is simple (4 params, no enums), so description is sufficient for a basic understanding. However, missing details on how output is structured (e.g., by family size) could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema documents all parameters well. The description does not add meaning beyond the schema (e.g., no explanation of FIPS codes or metro area codes). 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?
Clearly states it retrieves HUD income limits for housing programs by area, specifying eligibility categories (extremely low, very low, low) and family size. Distinguishes itself from sibling tools like hud_chas and hud_fair_market_rents.
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 use for determining income eligibility but does not explicitly state when to use versus alternatives like hud_chas or hud_fair_market_rents. No guidance on when to omit parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hud_list_statesAInspect
List all U.S. state codes and names. Returns state abbreviations and full names. Use to validate or discover state codes for other HUD tools.
| Name | Required | Description | Default |
|---|---|---|---|
| _apiKey | Yes | HUD API token |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states the tool lists codes and names, which implies a read-only operation. No annotations are provided, so the description carries the burden. It does not detail any destructive behavior or rate limits, but given the simplicity of the operation, the description is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. Front-loaded with the primary action and includes the 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 simple parameter set (one required string), no output schema, and straightforward purpose, the description is complete. It tells the agent what the tool does and why it is useful.
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 parameter '_apiKey' documented in the schema. The description does not add extra meaning about the parameter beyond the schema, but the schema already fully describes it. 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 clearly states the tool lists U.S. state codes and names from the HUD API, with the specific verb 'list' and resource 'state codes and names'. It also distinguishes itself by mentioning its utility for discovering valid state codes for other HUD 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 explains when to use this tool: 'Useful for discovering valid state codes to use with other HUD tools.' It implies a preparatory or lookup context, but does not explicitly mention when not to use it or name alternative tools.
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 must disclose behavioral traits. It clearly states the two behaviors (retrieve by key or list all), the persistence across sessions, and implies a storage mechanism. However, it does not mention side effects (e.g., if recall is destructive, if it requires special permissions, or what happens if the key doesn't exist). Still, the description is fairly transparent for a simple read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action ('Retrieve a previously stored memory by key, or list all stored memories') and then provides usage guidance. Every part earns its place 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 simplicity (single optional parameter, no output schema), the description is complete enough. It covers both modes and mentions cross-session persistence. Minor omission: it doesn't specify what happens if the key does not exist (error vs empty result), but for a simple retrieval 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?
The input schema has 100% coverage: the only parameter 'key' is described in the schema and the description adds context on when to omit it. The description goes beyond the schema by explaining the dual behavior (retrieve vs list) and the session persistence, which enriches the parameter's meaning.
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 ('memory by key') and clearly distinguishes the two modes: retrieving a specific key or listing all memories when key is omitted. It also hints at its use across sessions, which differentiates it from 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?
The description explicitly states when to use this tool ('to retrieve context you saved earlier') and when to omit the key ('to list all stored memories'). It provides clear guidance on both modes, and the context of 'session or previous sessions' helps the agent decide when to use recall versus remember or forget.
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?
No annotations provided, so description carries full burden. It discloses memory persistence behavior (authenticated vs. anonymous) and intended use. Does not mention overwrite behavior or limits, but adds meaningful context beyond schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with clear purpose, usage examples, and persistence details. 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?
For a simple key-value store with no output schema, the description covers purpose, persistence, and typical use. Missing details on overwrite behavior or maximum length, but overall sufficient for agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with descriptions for key and value. The description adds value by providing examples of what keys could be (e.g., 'subject_property'), but does not elaborate on value format beyond 'any text'. Baseline 3 is appropriate as schema already does 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 clearly states the tool stores a key-value pair in session memory. It specifies the verb ('store'), resource ('key-value pair'), and context ('session memory'), distinguishing it from recall and forget siblings.
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 use cases ('save intermediate findings, user preferences, or context across tool calls') and distinguishes between authenticated (persistent) and anonymous (24h) sessions. However, it does not explicitly contrast with forget or recall, which are siblings.
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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