psychopathia-mcp
Server Details
Read-only tools over the Psychopathia Machinalis nosology: 79 conditions, 11 tools.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Full call logging
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
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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 3.3/5 across 11 of 11 tools scored. Lowest: 2/5.
Each tool has a distinct function: differential diagnosis, dysfunction details, probes, listing with filters, ID resolution, etc. There is no overlap; an agent can clearly distinguish them.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_dysfunction, list_axes, score_severity). The naming is predictable and uniform.
With 11 tools covering diagnostic listing, retrieval, probing, severity, interventions, and review statistics, the count is well-scoped for the server's purpose. No tools feel extraneous or missing.
The set covers most core workflows: querying dysfunctions, diagnostics, interventions, and transparency. Minor pending features (embedding re-rank, structured matching) are noted but do not create critical gaps.
Available Tools
11 toolsdifferential_diagnosisBInspect
Rank candidate dysfunctions matching the observed behaviours. Returns scored candidates with matched_in (which field matched) for transparency. Field-weighted keyword search (v0.1); embedding re-rank pending v0.2.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| observations | Yes | Observed behaviours, symptoms, or log patterns. | |
| modality_hint | No | Optional hint about which modality the observations come from. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must cover behavioral traits. It discloses the search methodology (field-weighted keyword search, v0.1, future embedding re-rank) and return format (scored candidates with matched_in). However, it does not disclose whether the tool has side effects, authentication needs, or rate limits. The transparency is adequate for a read-only diagnostic tool 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?
The description is concise, consisting of two sentences that convey the core functionality and methodology. It is front-loaded with the action. Every sentence adds value, and there is no redundancy. A slight improvement could be removing the versioning detail, but it remains 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 tool has no output schema, the description explains the return format ('scored candidates with matched_in'). It also describes the search method. However, it lacks details on scoring interpretation, result limits, and any usage prerequisites. With moderate complexity, the description is minimally adequate but could be enriched to fully inform the 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 coverage is 67% (two of three parameters have descriptions). The description adds no additional meaning beyond the schema; it merely restates the parameter purposes. For the missing description on 'limit', the description provides no guidance. Since coverage is not >80% and the description does not compensate, the score is low.
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: 'Rank candidate dysfunctions matching the observed behaviours.' It specifies the action (rank) and the resource (candidate dysfunctions). However, it does not explicitly distinguish this tool from siblings like get_differential_map or list_dysfunctions, but the unique combination of ranking based on observations provides enough clarity.
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 the tool is for querying dysfunctions based on observed behaviors, but lacks explicit guidance on when to use it versus alternatives. No 'when not to use' or exclusion criteria are provided. The mention of versioning hints at current limitations but does not direct the agent to other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_differential_mapCInspect
All dysfunctions that confuse with this one: forward confuses_with + incoming_references (reverse graph from manifest).
| Name | Required | Description | Default |
|---|---|---|---|
| dysfunction_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as read-only status or side effects. The cryptic explanation does not help the agent understand what the tool does beyond its name.
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 short, but it is not clear or well-structured. It is not concise in a helpful way because it sacrifices clarity for brevity.
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 and insufficient parameter documentation, the description leaves the agent with significant uncertainty about the tool's output and usage. It is incomplete for a tool with one required parameter.
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 0%, and the description adds no meaning to the sole parameter 'dysfunction_id'. The agent receives no guidance on what value to provide or how it relates to the tool's function.
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 is vague and lacks a clear verb. It states 'All dysfunctions that confuse with this one' but does not explicitly say it returns a list or map. The phrasing 'forward confuses_with + incoming_references (reverse graph from manifest)' is cryptic and fails to convey the tool's primary action.
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 siblings like 'differential_diagnosis' or 'get_dysfunction'. It does not specify prerequisites or scenarios where this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_dysfunctionAInspect
Fetch one dysfunction's full Pattern entry. Optionally filter to specific modality blocks (cheaper triage). Resolves both full Pattern IDs ('1.1::synthetic-confabulation') and display_ids ('1.1').
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Pattern ID or display_id. | |
| modalities | No | Optional subset of modality block names to return. Valid: self_probe, behavioral_signature, peer_observation, differential_diagnosis, severity, intervention, relational_signatures, normative_anchors, cross_references. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the burden. It correctly implies a read operation ('Fetch') and mentions 'cheaper triage' for modality filtering, but does not explicitly state idempotency, permission requirements, or other behavioral traits.
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 no redundancy. The main purpose is front-loaded, followed by optional features and ID resolution details. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the basic purpose and optional filtering, but without an output schema, it does not explain the structure of the returned 'full Pattern entry', leaving some uncertainty about the response.
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%, but the description adds value by explaining that the id parameter accepts both full Pattern IDs and display_ids, and that modalities parameter can be used for cheaper triage, which is not evident from 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 action ('Fetch'), the resource ('one dysfunction's full Pattern entry'), and distinguishes itself from siblings by mentioning optional modality filtering and ID resolution, which are not found in sibling tool names.
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 a full Pattern entry and optionally want to filter modalities for cheaper triage. However, it lacks explicit when-not-to-use guidance or alternatives, relying on sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_probeAInspect
Elicitation content for a specific diagnostic modality. If the modality is compromised or unavailable for this dysfunction, returns the unavailability notice + redirect_to alternatives. This is load-bearing transparency: callers cannot accidentally retrieve a self-probe for a compromised-self-report dysfunction.
| Name | Required | Description | Default |
|---|---|---|---|
| modality | Yes | ||
| dysfunction_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses important behaviors: returns unavailability notice + redirect if compromised, and prevents accidental self-probe retrieval.
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, each impactful. Front-loads purpose, then conditional, then transparency. 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?
Covers core behavior and edge case (compromised). No output schema, but description adequately specifies return types. Could mention error handling for invalid inputs.
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 0% and description does not explain parameters individually. Enum values are self-explanatory, but no additional meaning beyond 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?
Specific verb 'get' and resource 'probe', with clear scope (diagnostic modality). Distinguishes from siblings like 'get_dysfunction' and 'list_compromised_self_report' by focusing on elicitation content.
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?
Implies usage when needing elicitation content for a modality, but no explicit when-not-to-use or alternatives. The redirect behavior is mentioned, but not contrasted with other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_axesAInspect
Inventory of axes with dysfunction counts. Axes 2-10 are canonical (book Appendix A numbering). Hybrid entries (10.4-10.15, ratified into taxonomy v2.2) are reported as a separate sub-category.
| 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, the description conveys that the tool is read-only (inventory with counts) and discloses key behavioral details like canonical vs hybrid axes. It implies safety but could be explicit about being non-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?
Two sentences, front-loaded with purpose, no fluff. Every sentence adds necessary context.
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 remarkably complete: it names the inventory, specifies canonical and hybrid axes, and mentions counts. An agent can correctly infer the output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with full schema coverage. The description adds value by explaining what the output contains (axes, counts, hybrid sub-category), which is not inherent 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 tool provides an 'Inventory of axes with dysfunction counts' and specifies which axes are included (canonical 2-10 and hybrid 10.4-10.15), making its purpose distinct from siblings like list_dysfunctions.
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 does not explicitly state when to use this tool versus alternatives (e.g., list_dysfunctions, get_dysfunction). While the purpose is clear, an agent may benefit from guidance on choosing this tool over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_compromised_self_reportBInspect
Transparency: which dysfunctions cannot be reliably self-diagnosed. Includes compromised-motivational (subject conceals strategically), compromised-structural (signal lives below introspection), and legacy compromised.
| 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, the description carries full burden but only notes that these dysfunctions 'cannot be reliably self-diagnosed', which is a transparency hint. It does not disclose any other behavioral aspects such as data source, update frequency, or potential side effects. The three subtypes add context but not behavioral transparency.
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 two sentences, but the jargon ('compromised-motivational', 'compromised-structural') may reduce clarity. It gets to the point quickly but could be more accessible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks detail about the output format or structure. As a list tool, it should indicate whether it returns a list of strings, categories, or detailed objects. Without output schema, more context is needed for 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 tool has no parameters and schema coverage is 100%, so the description does not need to add parameter semantics. Baseline 4 is appropriate because there is nothing to improve.
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 dysfunctions that cannot be reliably self-diagnosed and enumerates three categories. However, it does not explicitly differentiate from sibling 'list' tools like 'list_axes' or 'list_dysfunctions', and the domain-specific jargon may obscure purpose for some agents.
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 is provided on when to use this tool versus alternatives. There is no mention of prerequisites, typical use cases, or scenarios where this tool is preferred over sibling tools like 'differential_diagnosis' or 'get_dysfunction'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_dysfunctionsAInspect
Filtered list of dysfunctions. Filter by axis, self_report reliability, or confidence. Every entry carries its reliability and review signals.
| Name | Required | Description | Default |
|---|---|---|---|
| axis | No | Filter by axis number (2-10; canonical only) | |
| confidence | No | ||
| self_report_reliability | No | Filter by self_report value: reliable | partial | scaffolded-only | unreliable | compromised-motivational | compromised-structural | compromised |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavior. It states the tool returns a list with reliability and review signals, implying a read-only operation. However, it does not explicitly confirm no side effects or mention any required permissions, leaving some 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 two sentences long, efficiently conveying the tool's purpose and key features. Every sentence adds value: first identifies what the tool is, second details filters and output characteristics. 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?
With no output schema, the description partially compensates by noting that each entry includes reliability and review signals. However, it omits important list-tool details such as pagination, sorting, result limits, or error conditions. Given the sibling tool count (11), more context would help agents choose 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 description coverage is 67% (2 of 3 parameters have descriptions). The tool description merely restates the filter options already in the schema (axis, self_report_reliability, confidence). It adds no new meaning or usage details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Filtered list of dysfunctions.' It specifies the filtering dimensions (axis, self_report reliability, confidence) and what each entry contains (reliability and review signals). This distinguishes it from siblings like get_dysfunction (single item) or list_axes (axes only).
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 when-to-use or when-not-to-use guidance is provided. The description does not contrast this tool with alternatives such as get_dysfunction or differential_diagnosis, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
resolve_idBInspect
Canonicalise a partial ID, display_id, slug, or dysfunction name. Always returns candidates; caller picks.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must convey behavioral traits. It states it always returns candidates and that the caller picks, which gives some insight. However, it does not specify what happens if no matches are found or the format of candidates.
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. The first sentence clearly states the action and inputs; the second describes the behavior. Information is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema. The description covers the basic purpose and behavior but omits details about return format, error handling, or behavior when no match exists. These gaps reduce 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 schema provides no description for the 'query' parameter. The description adds significant meaning by listing allowed input types: 'partial ID, display_id, slug, or dysfunction name'. This is essential for correct usage.
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 'canonicalise' and specifies the resource types: 'partial ID, display_id, slug, or dysfunction name'. It distinguishes the tool from siblings which focus on retrieving data rather than resolving identifiers.
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 lacks any guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical scenarios, or when to avoid using it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
review_statsAInspect
Coverage statistics: total entries; per-axis, per-confidence, per-self-report counts; pre-canonical count; unreviewed count; manifest/schema/pattern-layer versions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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. The description lists returned metrics but discloses nothing about behavioral traits (e.g., read-only, side effects, authentication needs, rate limits). Missing critical 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?
The description is a single sentence that front-loads the purpose with 'Coverage statistics:' followed by a concise enumeration. No wasted words, though restructuring into bullet points could improve readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters and no output schema, the description must fully convey what the tool returns. It lists many specific count types and version info, which is fairly complete for a fixed report. Minor gap: does not mention if counts are for all data or can be scoped.
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?
No parameters exist (schema has zero properties, 100% coverage). The description does not need to add parameter info, but it compensates by detailing the output structure, which is the primary semantic contribution. Baseline 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 clearly specifies the resource (coverage statistics) and enumerates the exact breakdowns: total entries, per-axis counts, per-confidence counts, per-self-report counts, pre-canonical count, unreviewed count, and version info. It distinguishes this tool from siblings like list_axes or differential_diagnosis as a statistical summary tool.
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. Does not mention ideal scenarios, prerequisites, or exclusions. The agent must infer usage from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
score_severityCInspect
Return the severity rubric for a dysfunction applied to observations. v0.1 returns the rubric for caller-side matching; v0.2 will perform structured matching against numeric thresholds.
| Name | Required | Description | Default |
|---|---|---|---|
| observations | Yes | ||
| dysfunction_id | Yes |
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 only mentions version differences (v0.1 rubric for caller-side matching, v0.2 structured matching). No disclosure of side effects, permissions, rate limits, or output format.
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, concise and front-loaded with the main action. Version note is secondary but could be less distracting. No unnecessary 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 tool with 2 required params, no output schema, and no annotations, the description is insufficient. It defines the input but not the return format (rubric structure), how to interpret it, or any caveats. Agents would lack critical context for successful invocation.
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 0%. Description only indirectly references dysfunction_id and observations but does not explain what observations are (e.g., free-text symptoms, numeric values) or any constraints. No additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a severity rubric for a dysfunction applied to observations. The verb 'Return' and resource 'severity rubric' are specific. However, the version note (v0.1 vs v0.2) adds slight ambiguity about current behavior.
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 compared to siblings like get_dysfunction or differential_diagnosis. No explicit when-not-to-use or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
suggest_interventionBInspect
Return tiered (first_line / second_line) interventions for a dysfunction, plus contraindications. first_line = published evidence; second_line = plausible but under-validated. Weight by the evidence_strength field on each entry.
| Name | Required | Description | Default |
|---|---|---|---|
| severity | No | ||
| dysfunction_id | Yes |
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 tier definitions (first_line=evidence, second_line=plausible) and weighting by evidence_strength. However, it does not state if the tool is read-only, any side effects, or access requirements. Adds useful but incomplete 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, front-loaded with purpose. Second sentence adds critical detail on tier logic and weighting. Every sentence is valuable and 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?
No output schema; description partially fills gap by explaining tiers and weighting, but omits contraindication details and return format. Missing parameter usage context for severity. Adequate but not comprehensive.
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 0% and description does not explain parameters. 'dysfunction_id' and 'severity' are not elaborated; severity's enum values (mild/moderate/severe) lack context. Description focuses on output, not input 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?
Description clearly states the tool returns tiered interventions (first_line/second_line) for a dysfunction, plus contraindications. The verb 'return' and resource 'interventions' are specific. It distinguishes from siblings like 'differential_diagnosis' or 'get_dysfunction' by focusing on treatment suggestions.
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 when-to-use or when-not-to-use guidance. The description implies use after identifying a dysfunction, but does not compare to sibling tools or provide exclusion criteria. Usage context is only implied.
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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If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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