seshat-bi
Server Quality Checklist
Latest release: v2.0.0
- Disambiguation5/5
Each tool targets a distinct aspect of readiness: overall status, next action, blockers, evidence pack assembly, approval request preparation, and static checks. The descriptions explicitly cross-reference each other and clarify 'not for' cases, making misselection unlikely.
Naming Consistency5/5All six tools follow a consistent pattern: 'seshat_' prefix plus a verb_noun combination (get_status, get_next_action, explain_blockers, export_evidence_pack, prepare_approval_request, run_static_check). Naming is uniform and predictable.
Tool Count5/5Six tools is well-scoped for the server's purpose. Each tool covers a distinct operation within readiness governance, and none feel redundant or superfluous.
Completeness5/5The tool set comprehensively covers the read-only readiness governance domain: status, next step, blockers, evidence export, approval preparation, and static checks. It intentionally avoids write operations, but for its stated scope (reports and preparation only) there are no obvious gaps.
Average 4.7/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description reinforces this with 'reads committed files under the workspace and writes nothing,' adding the specific data source. It also discloses the outcome contract ('Outcome is ok unless an input is malformed') and the return projection, going beyond mere annotation repetition.
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, front-loaded with the core function, then structured into 'Use when', 'Not for', 'Returns', and 'Outcome' sections. Each sentence contributes a distinct piece of actionable information, with no 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?
The tool has simple inputs (2 params), a rich output schema, and strong annotations; the description covers the reading behavior, return shape, and outcome semantics. Sibling exclusions and usage context are addressed, leaving no major gaps for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with detailed descriptions for both parameters (workspace path constraint, table constraints including directory matching and forbidden characters). The description adds little new parameter detail, but it does clarify scope semantics ('one table's stage' vs 'overall readiness picture'), consistent with the schema. Therefore baseline score of 3 is appropriate.
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 clear action ('Report which readiness stage each table currently sits in'), naming the resource (readiness stages per table) and the scope (each table). It differentiates from siblings by naming 'seshat_explain_blockers' and 'seshat_get_next_action' as distinct tools, making the primary 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 Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit 'Use when' and 'Not for' conditions, including named alternative tools for related but different queries. This leaves no doubt about when to select this tool versus its siblings.
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 adds significant behavioral detail beyond annotations: 'Read-only: reports blockers and never clears, waives or overrides one.' It also explains the return format ('one entry per blocker... Outcome is 'blocked'...'). This complements the annotations without contradiction.
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: purpose, when to use, when not to use, return format, and safety note. Every sentence is purposeful and front-loaded, with no filler. Despite multiple paragraphs, each clause provides distinct value.
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 tool is a diagnostic read operation with no side effects; the description covers purpose, usage, output format, and limitations. With output schema present and safety annotations provided, this is fully complete for an agent 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.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters documented), so baseline is 3. The description adds no extra parameter-level detail beyond the schema; it only refers to 'one table' and 'named table,' which is already implied. No additional syntax or format info is provided.
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: 'Explain what blocks one table's next stage, and who can clear it.' The verb 'explain' and resource 'blockers' are specific, and the 'Not for' section explicitly differentiates from sibling tools (seshat_get_status, seshat_get_next_action), 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 Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage guidance is explicit: 'Use when: a table is not advancing...' and 'Not for: an all-table overview (use seshat_get_status) or picking the next step (use seshat_get_next_action).' This provides clear context and names alternatives, which is ideal for agent decision-making.
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?
Discloses read-only behavior ('Read-only: creates nothing on disk'), corrects the misleading name, and explains the return projection and the 'input_defect' outcome. This goes beyond the annotations by adding functional context and edge-case behavior.
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 brief, front-loaded with the core action, and uses explicit labeled sections (Use when, Not for, Returns, Read-only). Every sentence adds value 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?
With only two params, a high-coverage schema, and an output schema present, the description covers the essential context: purpose, exclusions, return value, error outcome, and safety. It is complete for an agent 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.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add significant param-specific detail beyond what the schema already provides; it only references 'the named table' without elaborating on parameter formats or constraints.
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 specific verb and resource: 'Assemble one table's evidence pack in memory and return it as data.' It explicitly distinguishes itself from file export ('despite the name nothing is exported') and from sibling tools by focusing on in-memory assembly for review or handoff.
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 'Use when' and 'Not for' conditions: use for reviewing/handing off evidence as structured data, not for writing to disk. This clearly signals when to choose this tool over a CLI-based file export, and the context is unambiguous.
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 states 'Read-only: names the action but never performs it, and grants no approval,' adding context beyond the readOnlyHint and idempotentHint annotations. It also reveals the 'blocked' outcome condition, which is useful behavioral information.
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 clear sections (Use when, Not for, Returns, Read-only) and every sentence provides distinct value. It is appropriately sized with no redundant 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?
Given the output schema exists, the description still provides key behavioral details, return format, and exclusions. It covers the tool's purpose, usage, limitations, and side effects (none), making it fully complete for an agent to decide when and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% description coverage for all parameters, including detailed semantics for requested_scope. The description adds the high-level use case of checking an intended action but no parameter-specific details beyond the schema. Baseline 3 is appropriate.
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 'Return the one action readiness allows now, and refuse anything past it,' which is a specific verb+resource statement that clearly conveys the tool's function. It also distinguishes from siblings by naming seshat_get_status and seshat_explain_blockers as alternatives.
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?
The description explicitly provides a 'Use when' section and a 'Not for' section with named sibling tools, giving clear guidance on when to use this tool versus alternatives. It also mentions checking an intended action, which is a key use case.
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 adds behavioral details beyond the annotations: it explains the return status 'prepared_not_approved', states that the outcome is always 'blocked' by design, and clarifies that it writes no approval receipt and grants no readiness. These details align with the readOnly/idempotent annotations but provide richer context.
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 'Use when', 'Not for', 'Returns', and 'Outcome' sections, and every sentence carries useful information without redundancy. It is concise while being thorough.
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, the description covers when to use, what it returns, and its side-effect-free behavior. With an output schema present, it fully equips the agent to decide when to invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers all three parameters with descriptions, and the schema description coverage is 100%, so the baseline is 3. The description does not add further parameter semantics beyond what the schema already provides.
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 'Draft the request a named human must rule on, approving nothing,' which states a specific verb and resource and clearly distinguishes this tool from approval actions. It is obviously different from sibling tools that query status or run checks.
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?
The description provides explicit when-to-use and when-not-to-use guidance: 'Use when: readiness needs a human ruling...' and 'Not for: granting, recording or standing in for an approval.' It also notes that no tool in the set can perform approval, thereby covering alternatives.
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?
Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses concrete behavioral details: it opens no database connection, writes no file, returns a boundary object recording live_validation as 'not_run', does not claim semantic correctness, and sets outcome to 'blocked' on error severity. This significantly enriches the agent's understanding.
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: a one-line action, followed by clear use-cases, return behavior, and read-only note. Every sentence earns its place with 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?
With one parameter, an output schema, and a clear explanation of return values (findings plus boundary object) and outcome semantics, the description provides a complete picture for an agent 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.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage for the single parameter 'workspace' is 100% with a clear description including path resolution and refusal constraints. The tool description adds no extra parameter semantics, so it rightfully relies on the schema; the baseline of 3 is appropriate.
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 specific verb+resource: 'Run the static governance rules and state what was not checked.' This clearly distinguishes it from siblings like seshat_get_status or seshat_export_evidence_pack by focusing on rule execution and explicit scope.
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?
The description contains explicit 'Use when' and 'Not for' sections, specifying when to use the tool (committed SQL/TMDL/PBIR/readiness artifacts without a database) and excluding live data validation, pointing to a separate CLI operation. This fully addresses when-to-use and alternatives.
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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