identity-aiops
Server Quality Checklist
Latest release: v0.7.0
- Disambiguation5/5
Each tool targets a distinct resource or analytical view: listings vs. details, per-user vs. per-client sessions, aggregate audits vs. raw event feeds. Even closely related tools like client_sessions and user_sessions are clearly separated by their subject. There is no meaningful overlap that would cause misselection.
Naming Consistency4/5Naming is generally snake_case and predictable, with list_* for collections (list_users, list_clients), noun_detail for single entities (client_detail, user_detail), and verb-first for writes (disable_user, rotate_client_secret). Minor deviations exist, such as identity_overview and client_session_stats not following the list_ or _detail pattern, but the naming style is coherent enough.
Tool Count2/5With 29 tools, the set is beyond the 25+ threshold for 'too many' and feels heavy. While each tool has a distinct purpose, the breadth could be consolidated (e.g., combining related audits or analyses into parameterized tools). This count may increase agent cognitive load and selection difficulty.
Completeness3/5The server provides strong read coverage (users, clients, sessions, events, audits) and security-focused writes (disable, revoke, rotate, reset), but lacks basic lifecycle operations such as create/delete user, create/delete client, group management, or an explicit unlock tool. These are notable gaps for a comprehensive identity management surface, though the existing tools cover common incident-response workflows.
Average 4.5/5 across 29 of 29 tools scored. Lowest: 3.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 20 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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This repository includes a glama.json configuration file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explicitly labels the operation as [READ] and describes the settings it retrieves, which is helpful. However, it does not disclose output format, error behavior, or any potential side effects. This is adequate for a read tool but not highly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. The [READ] prefix immediately signals the operation, the purpose is stated in one line, and the argument documentation is clear. Every sentence earns its place with no unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and no output schema, the description covers the essential aspects: the tool's function and parameter semantics. It could be improved by specifying the return format or typical error cases, but given the simplicity, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no descriptions for the 'target' parameter, but the description's 'Args: target: IdP target name from config; omit for the default' adds clear meaning. It explains the parameter's purpose and default behavior, effectively compensating for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads realm/instance settings related to identity hygiene, listing specific categories (brute-force protection, password policy, OTP policy, registration). The [READ] prefix indicates the verb, and the resource is specific. However, it does not explicitly differentiate from sibling tools like identity_overview, so it gets a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description explains what it does but does not mention alternative tools, exclusion criteria, or prerequisites. The argument documentation is present but only explains the parameter, not when to invoke the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adds the [READ] marker and clarifies the ID type, but it doesn't disclose return format, error handling, or rate limits. For a simple read tool, this is a moderate level of transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured, with a one-sentence summary followed by an Args list. There is no verbose or redundant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter read tool, the description covers core usage but does not describe the output format or what 'normalized detail' includes. Given the lack of an output schema, this gap prevents a higher score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema coverage, the description explains both parameters: client_id as an internal id from list_clients and target as an optional IdP target name from config. This adds necessary semantic context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves one client's normalized detail by internal id, which distinguishes it from list_clients and other client-related tools. The [READ] prefix further clarifies the operation type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It references list_clients as the source for client_id, providing clear context on when to use this tool. It also explains the optional target parameter, though it does not explicitly mention alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It includes a '[READ]' prefix indicating read-only operation, describes what the audit detects, and crucially explains truncation behavior ('inputsTruncated', 'truncated') and the guarantee that *Count fields are full totals. This is substantial behavioral context, though it stops short of discussing auth requirements or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a lead summary, an Args section, and a Returns note. It is a bit longer than a one-liner, but every sentence adds necessary information—parameter details and truncation behavior. No filler or redundancy is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description provides essential return-field context ('inputsTruncated', 'truncated', '*Count fields') and clearly lists the types of findings. It covers all three parameters and their defaults. It does not describe the full output structure or potential error conditions, but for a read-audit tool with this parameter set, the description is quite complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate fully. It does so by providing an Args block that explains each parameter's meaning (idle threshold, users to pull, IdP target name) and notes defaults. This adds value beyond the bare schema properties and makes the tool safely invocable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a dormant-access audit and enumerates specific categories: enabled users idle > N days, accounts that never signed in, service accounts with interactive logins, and orphaned sessions. This goes far beyond the tool name and distinguishes it from sibling audit tools like mfa_coverage_analysis or client_misconfig_audit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for auditing stale/dormant access, but it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or for which scenarios one should prefer a sibling tool. The context is clear enough to infer its purpose, but explicit guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 adds valuable context by stating the output is 'normalized user rows' and that 'truncated measured rather than guessed'—revealing how pagination works. This goes beyond a simple read operation description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with separated Args and Returns sections, and every sentence provides meaningful detail. It is concise without unnecessary fluff, using a clear [READ] prefix and compact param explanations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with no output schema, the description provides a complete picture: it details all parameters, the return object structure, and even the truncation semantics. It lacks only error-case or permission-related context, which is not critical for this operation given its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an Args section that explicitly explains each parameter beyond the schema: group_id source ('from list_groups'), max_results definition ('Page bound (default 200)'), and target meaning ('IdP target name from config; omit for the default'). This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the resource ('Members of one group') and the operation ('[READ]'), and it distinguishes this from sibling tools like list_groups, which lists groups themselves. The 'normalized user rows' detail further clarifies the output format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating that group_id comes from list_groups, and it notes target is for a specific IdP. However, it does not explicitly state when to prefer this over alternatives (e.g., user_detail or list_users) or provide exclusion criteria, so guidance is only implicit, not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must communicate side effects and behavior. The '[READ]' marker signals a non-mutating operation, and 'one-shot summary' suggests a bounded/fast response. However, it doesn't mention auth requirements, rate limits, output format, or what happens with the default target, leaving some burden unmet.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two compact sentences plus an Args line; every sentence adds information. The 'Lead with this' instruction earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single optional param and no output schema, the description adequately covers the tool's role and return contents. It could be slightly richer (e.g., mention whether failed-login feed size is a count or a list), but for the intended overview purpose it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema provides no description (0% coverage), only an optional 'target' with default null. The description fully clarifies that it is an IdP target name from config and that omitting it selects the default, which is all the agent needs for this single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with '[READ]' and explicitly states the tool produces a one-shot summary with a specific inventory (platform/realm, counts, failed-login feed size). It also instructs 'Lead with this,' making clear this is the entry-point overview tool and distinguishing it from the detailed sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It says 'Lead with this,' which tells the agent to use it as the initial overview before querying details. It does not explicitly name alternatives or exclusion criteria, but the directive is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It clearly signals a read-only operation via '[READ]' and discloses important behaviors: normalization of fields, truncation flag semantics, and null field handling. It does not mention permissions or rate limits, but for a list operation with return-format detail, this is strong coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the [READ] tag and clear purpose. The Args and Returns sections are concise, and every sentence adds value—especially the clarification about truncated measurement and null pkceMethod. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, no output schema, and no annotations, the description provides complete context: purpose, parameter semantics, return structure, and edge-case behavior (truncated flag, null fields). It is self-contained for an agent to invoke correctly. Additional details like error handling are unnecessary for this level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), so the description fully compensates. It explains max_results as 'Page bound (default 200)' and target as 'IdP target name from config; omit for the default', adding meaning beyond the bare parameter names. There is no ambiguity about how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('list') and resource ('OAuth/OIDC clients in the realm'), with normalization details. This distinguishes it from sibling tools like client_detail (which focuses on a single client) and other list tools (e.g., list_users, list_identity_providers).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the verb 'list' and the parameters, but there are no explicit when-to-use or when-not-to-use instructions, and no mention of alternative tools. For instance, it does not clarify when to use this instead of client_detail or client_sessions. The target parameter guidance is present but limited to configuration context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It explicitly labels the operation as [READ], discloses that one credential list is pulled per user (bounded), and explains the inputsTruncated flag and its implication for coveragePct being sample-based. This gives meaningful behavioral insight beyond a simple read.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a summary line, an Args section, and a return-value note. Every sentence contributes to understanding the tool's behavior, and the [READ] flag is front-loaded for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the core purpose, parameters, and a key return flag (inputsTruncated). It lacks a detailed list of all output fields, but the purpose statement already mentions the main outputs (overall %, users without MFA, factor types). Given no output schema and no annotations, this is reasonably complete but could be enhanced with a structured return description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully explain the parameters. It does so effectively: max_users is described as the sample size (default 200, one API call each), and target is identified as an IdP target name with an option to omit it for the default. This adds clear meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: analyzing second-factor coverage, including overall percentage, users without MFA, and factor types counted. This specific verb+resource combination distinguishes it from sibling tools like user_credentials or identity_overview.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for realm-wide MFA coverage analysis but does not explicitly mention when to use this instead of alternatives (e.g., user_credentials for individual users). It provides useful context about bounded sampling and the max_users parameter, but lacks direct comparison to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility. It clearly discloses that the action is IRREVERSIBLE, that there is 'no undo,' and that the prior session count is recorded for audit. The dry_run preview option is also disclosed. This goes beyond a minimal statement of effect and gives critical safety information, though it stops short of describing exact return values or permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: the action, risk level, and irreversibility are stated first, followed by a clean parameter list. Every sentence adds value, and there is no repetition of schema fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no output schema and no annotations, the description covers the action, side effects, audit trail, dry-run capability, and parameter provenance. The only minor gap is an explicit statement of the return format, but the audit reference hints at what the user should expect. Overall it is sufficiently complete for a 3-parameter destructive tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain all parameters. It does so fully: user_id is sourced from list_users, dry_run is explained as a preview without revoking, and target is described as an optional IdP config reference. Each parameter receives practical, non-obvious context that the raw schema (titles only) does not provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a precise verb and resource: 'Revoke ALL of a user's sessions.' This clearly distinguishes it from sibling tools like user_sessions (read-only listing) and disable_user (disabling the account itself). The scope and irreversibility are highlighted immediately.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the verb 'Revoke' and the explicit 'ALL' scope, but no alternatives or when-not-to-use guidance is provided. The dry_run parameter implicitly suggests a preview workflow, but it does not explicitly contrast with read-only tools like user_sessions or other user management tools such as disable_user.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It discloses read-only behavior via '[READ]' and performance characteristics via 'cheap health probe', which is useful. It does not mention potential caveats like whether the count is real-time, includes disabled users, or requires specific permissions, leaving some behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a short purpose line followed by a one-argument explanation. Every sentence is useful, and the [READ] tag is front-loaded for immediate clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter, no output schema), the description is nearly complete. It covers purpose, use case, and argument semantics. It does not explicitly describe the return format or edge-case behavior, but 'Total user count' strongly implies a numeric response, making it sufficient for a simple health probe.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description fully compensates by explaining the sole parameter 'target' as an 'IdP target name from config' and stating that omitting it uses the default. This adds essential meaning beyond the raw schema definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Total user count in the realm' and labels it as a 'cheap health probe', giving a specific, distinct purpose. It differentiates from sibling list or detail tools by emphasizing it is a count and a lightweight probe.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'cheap health probe' implies usage for health checks and signals low overhead, a clear context. However, it does not explicitly mention alternatives or conditions when not to use it, so there is no direct comparison to sibling tools like list_users.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the disclosure burden. The '[READ]' prefix and mention of returning details indicate a non-mutating lookup. However, it does not discuss error behavior, permissions, or edge cases, leaving some behavioral transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: a clear one-line purpose followed by a concise Args list. Every sentence adds value, with no repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with two parameters and no output schema, the description covers the return value sufficiently (enabled state, required actions, attributes) and parameter sources. It lacks some edge-case guidance (e.g., invalid user_id), but overall is complete enough for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining user_id as 'Keycloak UUID / authentik pk, from list_users' and target as 'IdP target name from config; omit for the default'. This adds meaning beyond the bare parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads 'one user's full detail' with specific content (enabled state, required actions, attributes). It uses the verb 'READ' and specifies the resource, which distinguishes it from sibling tools like list_users or user_sessions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: user_id should come from list_users, and target is optional and defaults to default IdP. It implies when to use this tool (for a single user's full details) but does not explicitly contrast it with alternatives like user_credentials or user_sessions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that this is a read operation and details the return structure, including a 'truncated' flag that is 'measured rather than guessed,' which provides valuable insight into pagination behavior. It does not discuss error conditions or authorization, but for a simple list operation, it is sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured with sections for purpose, arguments, and return value. Each sentence is informative and there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no annotations or output schema, the description provides all essential invocation details: purpose, parameter meanings/defaults, and return structure. The note about 'truncated' being measured rather than guessed adds useful specificity. For a tool of this simplicity, the description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description fully compensates by explicitly explaining both parameters: max_results as a page bound with default 200, and target as an IdP target name that can be omitted. This adds clear semantic meaning beyond the bare property names and types in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly labels the operation as '[READ]' and specifies the resource 'Groups in the realm,' which clearly distinguishes it from sibling tools like list_users, list_clients, and list_identity_providers. The verb and resource are clear and specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing groups based on the resource name, but it does not explicitly state when to choose this tool over alternatives like group_members or list_users. No exclusions or alternative recommendations are provided, so guidance is minimal and only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It begins with '[READ]' to signal read-only behavior, and explicitly discloses that the IdP returns the complete set and is never truncated. This adds valuable behavioral context beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured with separate Args and Returns sections. Every sentence adds value: what it does, the parameter, and the truncation guarantee. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given 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 complete. It provides the return structure, mentions the no-truncation behavior, and covers the parameter. Nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single optional parameter 'target' is fully explained in the description ('target: IdP target name from config; omit for the default'), which goes far beyond the schema's bare 'default: null'. This fully compensates for the schema's 0% description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'lists federated identity providers / sources configured on the IdP', using a specific verb and resource. It is distinct from sibling tools like list_clients, list_users, and list_groups by focusing on identity providers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for enumerating configured identity providers but does not explicitly contrast with alternatives or mention when not to use it. It lacks the explicit 'use this instead of X when...' guidance seen in higher-scoring examples.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 explicitly labels the operation as '[READ]' and states that the IdP returns the whole session set, ensuring the listing is always complete. This goes beyond a simple read label and provides useful context about no truncation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the core verb and object. Every sentence serves a purpose: the first line states what it does, the Args block explains parameters, and the Returns block specifies the output contract. No redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with no annotations or output schema, the description is remarkably complete. It covers the return shape, parameter provenance, and the completeness guarantee. It addresses the key information an agent needs to invoke and interpret the result correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates fully by explaining both parameters: user_id is sourced from list_users, and target is an IdP target name from config with an explicit omit-for-default instruction. This provides all necessary semantic meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ] A user's active sessions' and lists the returned fields (id, IP, start/last access, clients), clearly identifying the resource and action. It also distinguishes itself from sibling tools like client_sessions (client-scoped) and revoke_user_sessions (mutation) by focusing on a single user's active sessions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The user-specific scope implies when to use the tool, and the argument guidance ('user_id from list_users', 'target from config') provides context. However, it never explicitly contrasts itself with alternatives like client_sessions or states when not to use it, so the usage guidance remains implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full responsibility. It discloses that this is a write operation with high risk, that it is reversible, and that dry_run previews without changing. It also clarifies the risk label is descriptive, not an enforcement gate. This is thorough, though it omits error behavior or postconditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded, with a clear risk header, a brief explanatory paragraph, and a concise args list. Every sentence adds value, and the structure makes it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description covers purpose, risk, usage caveats, and all parameters. It notably explains the risk=high tag and dry_run behavior. A minor gap is the lack of explicit success/error indicators, but the given context is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only names and types with no descriptions (0% coverage). The description compensates fully: user_id sources from list_users, dry_run previews without changing, and target defaults when omitted. This adds meaningful context that is absent from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[WRITE][risk=high] Re-enable a user (restores sign-in); reversible,' which clearly states the action and its effect. It unambiguously identifies the tool's purpose and naturally distinguishes it from siblings like disable_user.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when it is appropriate by noting it reverses a containment action, and it advises that execution depends on agent judgement or account permissions. It also recommends using dry_run=True for preview. However, it does not explicitly compare against alternatives like undo_apply, though this is an implicit distinction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility. It discloses the '[READ]' nature, the return behavior including 'feedTruncated' and lower-bound counts, and that findings include numbers, cause, and action. It does not cover all possible side effects or prerequisites, but for a read-only analysis tool it is quite transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a succinct purpose line, a clear args list, and a crucial return-value caveat. No redundant or filler sentences; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description covers purpose, parameters, and key return behavior (feedTruncated). It does not detail the exact structure of findings but indicates each includes numbers, cause, and action. This is sufficient for an agent to select and invoke the tool correctly, though more detail on return format could push it to 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameters. It does so effectively: window_minutes as trailing window, max_events as event pull count, target as IdP name with omit-to-use-default semantics. This adds crucial meaning beyond the schema's types and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs RCA over the failed-auth feed and enumerates specific categories (brute-force, misconfigured client, expired-credential storm, lockout storm), distinguishing it from sibling tools like login_events or client_misconfig_audit. The verb 'RCA' and the resource 'failed-auth feed' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly sets context for when to use it (RCA of failed logins) but does not explicitly mention alternatives or exclusion cases. It lacks explicit when-not-to-use guidance, but the context is sufficiently clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the write nature, risk tier, that the inverse tool is governed/audited, that dry_run exists, and that tokens are single-use. This is substantive but could elaborate on error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: a header line, a brief paragraph with key constraints, and a clean Args list. Every sentence provides necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a write tool with no output schema and minimal annotations, the description covers core behavior: purpose, dry-run mechanism, one-time use, and parameter roles. It lacks error-condition details but is otherwise comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides meaningful explanations for all three parameters beyond the schema: undo_id's source, dry_run's effect, and target's passthrough behavior. This fully compensates for the 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[WRITE][risk=medium] Apply a recorded undo by dispatching its inverse tool,' which clearly states the action (apply) and the resource (recorded undo). It distinguishes itself from undo_list by explaining the mechanism, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It instructs users to pass dry_run=True to preview without executing, and notes that a token can only be applied once. It also references undo_list as the source for undo_id, implying a workflow. However, it does not explicitly compare to alternatives or state when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full safety burden and includes the '[READ]' prefix to signal a read-only operation. It also discloses the return format and the nuanced behavior of 'truncated' on authentik, which is valuable beyond what structural fields would provide. It does not cover permissions or rate limits, but for a read tool this 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with Args and Returns sections, front-loads the core purpose, and every sentence contributes useful information. It is concise enough while capturing important details, with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's purpose, parameter semantics, return structure, and a platform-specific behavioral nuance, which is comprehensive for a tool with only two optional parameters and no output schema. The explicit return format documentation is particularly valuable given the lack of an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description thoroughly compensates by explaining max_results as a page bound with default and max, and target as the IdP target name with the 'omit for default' instruction. This adds meaning well beyond the schema's type definitions and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists 'Recent admin/config-change events' with details on who/what/from where, making the purpose unambiguous. The '[READ]' prefix further clarifies the operation type, and it distinguishes itself from siblings like login_events and client_detail by focusing on admin/config changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool (auditing admin changes) and provides parameter guidance for invocation. However, it does not explicitly mention when not to use it or name alternative tools, so it lacks the explicit exclusions needed for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the read-only nature ([READ]), platform-dependent error behavior, unbounded result set ('this listing is always complete'), and ordering ('busiest first'). It does not discuss permissions or rate limits, but for a read-only stats tool this 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear [READ] tag, purpose statement, platform caveat, Args section, and Returns section. Every sentence conveys useful information, and the inline error example is compact yet prevents unnecessary retries.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a listing tool with no output schema, the description adequately specifies the output shape (clients array, returned count, truncated flag), the unbounded nature, and the error case. It also notes the ordering and platform compatibility, making it complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'target' is clearly explained as 'IdP target name from config; omit for the default.' With schema coverage at 0%, the description fully compensates by adding the semantic meaning and optionality that the input schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Active-session counts per client, busiest first (Keycloak)', which is a specific verb+resource plus the aggregation scope and ordering. It distinguishes from sibling tools like client_sessions by focusing on per-client rollup counts rather than individual sessions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear platform constraints: 'KEYCLOAK ONLY' and explains that authentik will return an error object and should not be retried. It gives a usable when-not-to-use and error-handling instruction, though it does not explicitly name alternative tools for the same use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It clearly marks the operation as read-only, describes the return format, discloses that truncated is measured via an extra fetch, and states the null convention for missing IdP fields. It stops short of describing authentication requirements or error cases, but for a read-only list tool this is quite thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a clear summary and uses structured sections (Args, Returns). Every sentence provides value, including the truncation nuance and null convention. It is appropriately sized for a tool with three parameters and an edge case.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multi-IdP normalization, pagination, null handling) and the absence of an output schema, the description covers all essential aspects: purpose, parameters, return structure, truncation detection, and field conventions. An agent has enough information to invoke and interpret results correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description is the only source of parameter meaning. It explains search as a username/email search, max_results as a page bound with a default, and target as an IdP name from config with a default if omitted. This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies a clear action (list users) with a defined scope (in the realm, normalized across Keycloak/authentik). The [READ] prefix and explicit reference to 'users' distinguishes it from sibling tools like list_clients or list_groups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context for when to use the tool (realm-wide user listing, normalized across IdPs) and covers pagination behavior ('re-run with a higher max_results before drawing a realm-wide conclusion'). It does not explicitly name alternatives or exclusion cases, but its purpose is clear enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly discloses the truncation behavior ('truncated is measured (one extra event is fetched), not guessed') and the null-handling convention ('Optional fields ... are null, never \"\"'). These are valuable behavioral details beyond the bare read operation, especially since no annotations are provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tightly structured with 'Args' and 'Returns' sections, ~140 words, with every sentence contributing info (vocabulary, pagination semantics, null convention). No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description fully specifies the return shape ({\"events\": [...]}), the meaning of 'truncated', and how to handle partial feeds. It also covers all four parameters with actionable details, making the tool complete for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the 'Args' section adds substantial meaning: it defines the platform vocabulary for event_type (Keycloak LOGIN / LOGIN_ERROR, authentik login / login_failed), explains user as optional username/ID filter, gives max_results default (200) and max (500), and clarifies target as an IdP target name from config. This far exceeds the bare schema types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ] Recent authentication events' with a specific verb (read) and resource (authentication events), and lists normalized fields (time/type/user/ip/client/error). This clearly distinguishes it from sibling tools like admin_events (admin actions) and login_failure_rca (failure analysis).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for reading recent authentication events but does not explicitly mention when to use it instead of related tools (e.g., admin_events, login_failure_rca). No alternatives or exclusions are named, so guidance remains implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden: it declares [WRITE] and risk=medium, notes reversibility, clarifies that undo only affects flags set by this call, and mentions dry_run for preview. This covers key behavioral traits, though it doesn't detail authentication requirements or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description leads with a compact action statement and a useful risk tag, followed by a tidy args list. Every sentence adds value, and the format is scannable and front-loaded with the critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 4-parameter tool with no output schema, the description covers the main action, the undo behavior, the dry_run safeguard, and the target parameter. It provides enough guidance to invoke correctly without requiring external lookups, and the no-output-schema case is adequately handled since return values aren't specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description explains every parameter: user_id is sourced from list_users, clear denotes the undo path, dry_run previews without changing, and target specifies the IdP from config with a default. This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action: 'Require a password reset at next sign-in' with a clear resource (password reset) and context (Keycloak required actions). It also differentiates the undo path, distinguishing it from sibling tools like disable_user or revoke_user_sessions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear usage context, including the undo mode ('Pass clear=True to remove a pending requirement instead') and the reversibility condition. While it doesn't explicitly name alternative tools, the action is well-scoped and the guidance on when to use clear=True versus the default adds practical direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It opens with '[READ]' to indicate a safe read operation, and explicitly states return behavior including 'truncated': false and 'always the user's complete credential set.' This adds valuable behavioral detail beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with '[READ]'. The argument list is concise, and every sentence contributes necessary information—purpose, parameters, and return format—with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description provides the return structure and notes the invariant of returning the complete credential set. For a simple 2-parameter read tool, this is complete and gives the agent enough context to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates: it explains that user_id comes from list_users and that target is an optional IdP target name with a default behavior. Both parameters are given meaningful context beyond raw schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource: '[READ] A user's configured credentials/authenticators — the MFA surface.' It clearly identifies the tool's function and differentiates it from sibling tools like user_detail by focusing on MFA credentials.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear usage context is provided: 'user_id: User id, from list_users' and 'target: IdP target name from config; omit for the default.' It does not explicitly name alternative tools, but the read-only scope and parameter provenance make when-to-use reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
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 explicitly says '[READ]' indicating a non-mutating operation, and it proactively reveals a critical caveat: 'inputsTruncated' returns true when max_clients is hit, warning that a clean result over a clipped list is not evidence of a clean estate. This is valuable behavioral transparency beyond the basic read intent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded. It starts with a concise summary of the tool's purpose and risk categories, then clearly separates 'Args' and 'Returns' sections. Every sentence earns its place—even the caveat about inputsTruncated is essential context. It is compact but comprehensive, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema and no annotations, the description provides a good amount of context: it explains the main output (per-client riskScore, evidence, actions) and the truncation behavior. However, it does not fully specify the return structure (e.g., exact fields of each client object, shape of the response). It is complete enough for an agent to understand what is returned, but could be more explicit about the full output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for parameters, but the description fully compensates by explaining both parameters: 'max_clients: Clients to pull (default 200)' and 'target: IdP target name from config; omit for the default.' This adds meaningful semantics that the schema alone (types/defaults only) does not provide, such as the meaning of target and the truncation-related purpose of max_clients.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a read-only audit for OAuth/OIDC client misconfigurations, listing specific risk factors (wildcard redirect URIs, public clients with secrets, implicit flow, missing PKCE, password grant) and stating it produces per-client riskScore with evidence and actions. This is a specific verb+resource that distinguishes it from siblings like list_clients or client_detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: it is the tool to use for auditing ranked client risk, as evidenced by the enumerated misconfiguration categories and the audit-focused language. It does not explicitly exclude other tools or name alternatives, but its scope is unmistakable—there is no ambiguity about when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
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 and does so excellently. It discloses the write nature, risk level, reversibility, reading of the user first to record an undo, live session behavior, and the self-refusal safety guard.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized and front-loaded: a concise summary, then behavioral context, then parameter details. Every sentence adds value and no unnecessary repetition exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is rich for a mutation tool with no annotations or output schema. It covers behavior, side effects, arguments, and edge cases. It lacks explicit detail about return values or permission requirements, but the overall context is strong.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description's Args section is essential. It adds meaningful semantics for all three parameters: where user_id comes from, what dry_run does, and how target defaults. This fully compensates for the sparse schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Disable a user') with a clear scope ('blocks sign-in') and explicitly notes reversibility. This clearly differentiates it from sibling tools like enable_user and revoke_user_sessions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides strong usage context: it is the 'containment move for a compromised/stale account,' mentions pairing with revoke_user_sessions, and explains the dry_run preview mode. However, it does not explicitly state when not to use it or name direct alternatives, so it falls slightly short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the platform-specific error response and clarifies it is a definitive answer, not a fault. However, it does not describe the success return payload or other edge cases, leaving some gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose, then a critical platform caveat, then parameter explanations. Every sentence earns its place; no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple status tool with no output schema, it covers purpose, platform constraints, arguments, and error handling. It could be slightly more detailed about the successful return value, but overall it is complete enough for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions, but the description explains user_id originates from list_users and target is an IdP config name with a default. This adds meaningful semantics beyond the bare schema field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it reads brute-force lockout status for one user, explicitly scopes to Keycloak, and differentiates from sibling login_failure_rca. The verb and resource are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'KEYCLOAK ONLY', explains what happens on authentik, and directs to login_failure_rca as the alternative. It also provides 'do not retry' guidance, which is excellent usage instruction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It details the return shape, explains that truncated is measured (one extra row fetched), and warns that effectVerified=false means the change is only probable, not confirmed. This goes beyond a typical list tool description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but every sentence adds value. It is front-loaded with the core purpose and uses structured paragraphs for nuances like truncation and effectVerified, with an Args section for parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description must explain return values, which it does including the JSON structure and the meaning of truncated and effectVerified. It also covers limit caps and target's irrelevance, making it complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are fully explained: limit is described as max rows with default 50 and cap 500, and target is noted as unused but kept for CLI uniformity. This compensates for the schema's 0% description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ] List recorded, not-yet-applied undo tokens (most recent first).' This clearly identifies the verb (list), resource (undo tokens), and scope (not-yet-applied), distinguishing it from the sibling undo_apply which applies them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It directs the reader to use the undoId with undo_apply, providing a clear follow-up action. However, it doesn't explicitly state when not to use this tool or compare it to other list tools, so it falls short of a fully explicit usage policy.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral traits: it's a write operation, tagged risk=high, reversible via captured prior list, replaces rather than appends, and supports dry_run for preview. It also contextualizes the risk label as descriptive, not a gate, which is valuable nuance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: an opening summary with key tags, a behavior/context paragraph, and a clean Args list. Every sentence adds information, and no space is wasted on filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no annotations, and no output schema, the description fully covers the tool's behavior, reversibility, security context, parameter semantics, and safe usage pattern (dry_run). It provides all contextual information an agent needs to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must carry parameter meaning. It does this excellently: client_id is sourced from list_clients, redirect_uris is the complete new list, dry_run previews without changing, and target optionally selects an IdP. This adds semantic value beyond the schema's bare titles/defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'REPLACE a client's redirect-URI list'. The verb 'replace' plus the resource 'redirect-URI list' is specific, and the additional detail about replace-not-append and reversibility distinguishes it from any potential sibling operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: it's a high-risk write operation on a security boundary, should be used with the full desired list, and supports dry_run for preview. It also notes that client_id comes from list_clients. However, it does not explicitly name alternative tools or give when-not-to-use guidance, stopping short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the read-only nature ('[READ]'), the platform-specific error response format, and how to interpret it (as a capability answer, not a fault). It also specifies the return schema and truncation semantics, going well beyond the structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with a summary line, a platform caveat, an Args list, and a Returns section. Every sentence provides necessary context (platform limitations, error behavior, return shape) without fluff. It is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the platform-specific behavior, no output schema, and no annotations, the description covers all necessary context: return format, pagination/truncation, error handling, and parameter prerequisites. It is fully self-contained for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameters. It does so for all three: client_id ('Internal id, from list_clients'), max_results ('Page bound (default 200)'), and target ('IdP target name from config; omit for the default'). This adds real meaning beyond bare titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Active user sessions on one client (Keycloak).' It uses a specific verb ('list') and resource ('client sessions'), and explicitly distinguishes from sibling tools like user_sessions by noting this is per-client and Keycloak-only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when to use the tool ('KEYCLOAK ONLY') and provides guidance for alternative platforms: on authentik, switch to user_sessions per user rather than retrying. It also references list_clients as the source for client_id, which is a clear prerequisite.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It covers irreversibility, masked fingerprints, self-rotation refusal, dry_run behavior (refusal rather than preview), and the need to re-store credentials — far exceeding typical transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence earns its place: risk tag, action, irreversibility, the self-rotation edge case, operational update requirement, dry_run explanation, and parameter details. Structured with clear sections and no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without annotations or output schema, the description covers all essential context: safety, edge cases, parameter semantics, and post-rotation steps. The mention of masked fingerprints also indicates what will be returned, making it highly complete for a high-risk write operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the description's Args section explains each parameter: client_id's source (list_clients), dry_run's preview effect, and target's default behavior. This fully compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Rotate a client's secret' — a specific verb and resource. It distinguishes itself from sibling read tools like client_detail and list_clients by emphasizing irreversibility and write semantics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-not guidance: refuses to rotate the authenticating client, directing users to the admin console and the 'identity-aiops secret set' command as an alternative. Also notes operational requirements like updating deployments, making usage context clear.
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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