failmodes
Server Details
MCP server for the Fail Modes taxonomy — a knowledge base of AI system failure modes
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- elyngved/failmodes-mcp
- GitHub Stars
- 0
- Server Listing
- failmodes-mcp
Available Tools
4 toolsget_failure_modeAInspect
Retrieve the full structured record for a single failure mode by its ID slug (e.g. 'citation-hallucination', 'sycophancy').
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The failure mode ID slug, e.g. 'citation-hallucination' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states 'full structured record' but does not disclose any additional behavioral traits like authorization needs, rate limits, or potential side effects. As a read-only operation, minimal transparency is acceptable, 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?
The description is a single, well-structured sentence that front-loads the action and includes an example. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should compensate by hinting at what the 'full structured record' contains. It is vague and does not specify fields or structure, making it less complete for an agent expecting return value details.
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% for the single parameter 'id'. The description adds value by providing an example format ('citation-hallucination', 'sycophancy'), which helps the agent understand acceptable values beyond the schema's generic 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?
The description clearly states the verb 'Retrieve', the resource 'failure mode', and the identifier 'ID slug' with examples. It distinguishes itself from siblings (list_categories, list_modes, search_failure_modes) by focusing on a single record retrieval.
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 when to use: to get a single failure mode's full record. It does not explicitly state when not to use or alternatives, but the context is clear given sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesAInspect
List all taxonomy categories with their IDs, names, descriptions, and mode counts.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It correctly implies a read-only operation (listing) and specifies the output fields, adding value beyond the empty schema. However, it does not mention potential performance issues or ordering.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence that immediately conveys the tool's purpose and output 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 list tool with no parameters and no output schema, the description provides adequate information about what is returned. It could mention if authentication is needed or if the list is paginated, but the context of sibling tools suggests this is a straightforward catalog.
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?
There are no parameters, and schema coverage is 100% trivially. The description does not need to add parameter info. Baseline 4 is appropriate 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 tool lists all taxonomy categories and specifies the returned fields (IDs, names, descriptions, mode counts). This distinguishes it from sibling tools like get_failure_mode, list_modes, and search_failure_modes, which deal with different entities.
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 says 'list all taxonomy categories', making it obvious when to use this tool (to get a full list). It does not mention when not to use it or alternatives, but given the sibling tools are about failure modes and modes, there is minimal ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_modesAInspect
List failure modes, optionally filtered to a single category by category ID.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Optional category ID to filter by, e.g. 'factuality'. Omit to list all modes. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It only states the basic action and filtering, but omits important behavioral traits such as pagination, sorting, error handling, or whether the operation is read-only.
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 core purpose without any 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 list tool with one optional parameter and no output schema, the description is nearly complete. It could mention the return format (list of failure modes) but the core functionality is clear.
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 clear description for the single parameter. The description adds the action context but does not provide additional semantics beyond what the schema already offers.
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 (list) and resource (failure modes), and includes the filtering option by category ID. It distinguishes from siblings like get_failure_mode (single) and list_categories (categories).
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 (list all or filter by category) but does not explicitly say when to use this vs alternatives like search_failure_modes 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.
search_failure_modesAInspect
Search the Fail Modes taxonomy by symptom text or keyword phrase. Returns ranked matches with id, name, category, and matched context.
| Name | Required | Description | Default |
|---|---|---|---|
| symptom | Yes | Symptom phrase or keyword to search for, e.g. 'made up a citation' or 'refused to help after pushback' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure. It states the tool returns ranked matches with specific fields, which is appropriate for a search. However, it does not disclose whether it is read-only, any authentication needs, or potential rate limits. For a simple search tool, this is adequate but not thorough without annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief, using two short sentences with no redundant information. It front-loads the action and resource, then specifies the return format. Every word contributes to 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 simplicity of the tool (one parameter, no output schema), the description adequately covers its purpose, input, and output. It would benefit from mentioning when to use sibling tools, but overall it provides sufficient context for an AI agent to invoke it 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?
With 100% schema description coverage (the 'symptom' parameter is well-described in the schema), the description adds an example ('e.g. 'made up a citation''), which provides useful context but does not significantly enhance semantic understanding beyond what the schema already provides. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search'), the resource ('Fail Modes taxonomy'), and what it returns ('ranked matches with id, name, category, and matched context'). It distinguishes itself from sibling tools like 'get_failure_mode' (specific ID retrieval) and 'list_categories' (listing categories) by focusing on text-based searching.
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 a symptom phrase is available, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The required parameter 'symptom' is clear, but no context on when to prefer this over 'list_modes' or 'get_failure_mode'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
4 tool updates
- First observed
get_failure_mode - First observed
list_categories - First observed
list_modes - First observed
search_failure_modes
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Glama MCP Gateway
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TDQS
Each tool has a clearly distinct purpose: retrieving a single record by ID, listing categories, listing modes (optionally filtered), and searching by symptom text. No overlap or ambiguity.
All names follow a consistent verb_noun pattern using snake_case: get_failure_mode, list_categories, list_modes, search_failure_modes. The pattern is uniform and predictable.
Four tools is well-scoped for a read-only taxonomy explorer: one for retrieval, two for listing (categories and modes), and one for search. Each tool earns its place.
The tool surface covers all essential operations for exploring failure modes: listing categories, listing modes, searching, and getting details. No obvious gaps for the stated domain.