Server Quality Checklist

Tool Scores

• get_savings_statsA
  3.7/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  No annotations are provided, but the description implies a read-only operation via 'Get'. However, it does not explicitly disclose behavioral traits like side effects, rate limits, or authorization needs.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Single sentence, no wasted words. All information is front-loaded and efficient.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given no parameters and no output schema, the description covers the basic functionality but lacks details on return format or units of savings. Could be more specific about the analytics provided.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  There are no parameters (0, so baseline 4). The description adds value by specifying the type of analytics (token savings) and time periods, which goes beyond the empty schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the verb 'Get' and the resource 'token savings analytics', with specific time frames 'today/this week'. It distinguishes from siblings like get_graph_stats by focusing on token savings.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  No guidance on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or context for use.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• checkpoint_sessionA
  4/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  No annotations are provided, so the description carries the full burden. It discloses the destination ('graph memory') and the checkpoint nature, but does not mention side effects, permissions, or response behavior. Adds some context but lacks depth.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Three sentences with zero redundancy. Each sentence serves a purpose: action, benefit, and usage scenarios. Well-structured and front-loaded.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple one-parameter tool without output schema, the description covers what it does and when to use it. It could mention return/confirmation behavior, but overall it is complete enough for the tool's simplicity.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100% with a clear example ('my-project-auth'), so the description need not add parameter details. It does not, and the baseline of 3 is appropriate since the schema already documents the parameter.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses specific verbs 'Save' and 'Creates a checkpoint', clearly identifies the resource ('current AI session to TokenMizer's graph memory'), and distinguishes itself from the sibling resume_session by focusing on saving vs resuming.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  Explicitly lists three use cases ('finishing a work session, before switching tasks, or when the conversation is getting long'), providing clear context. However, it does not mention alternatives or when-not-to-use, though the sibling resume_session implies complementarity.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_graph_statsA
  4/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  No annotations provided, so the description carries the full burden. It discloses that the tool reads stats (non-destructive) and lists the types of stats. However, it does not mention any behavioral traits like required permissions, response format, or potential side effects, which are minimal for a read operation.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, front-loaded sentence that efficiently conveys the tool's action and output. Every word adds value, and there is no wasted content.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's simplicity (one parameter, no output schema), the description is reasonably complete. It explains what stats are tracked, though it could elaborate on whether stats are cumulative or per-session. Overall, it provides sufficient context for an agent to understand usage.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The description adds no extra meaning beyond the input schema. The schema already describes the session_id parameter with full coverage (100%), so the description's mention of 'session' is redundant. Baseline score 3 applies.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the purpose: to see knowledge graph stats for a session. It specifies what stats are included (tasks, decisions, files, errors), making the tool's function precise and distinct from sibling tools like analyze_file or get_savings_stats.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implicitly indicates when to use (when needing graph stats for a session) but does not explicitly state when not to use or mention alternatives. However, the standalone purpose is clear enough for typical scenarios.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• why_decisionA
  4/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  No annotations provided, so description carries full burden. It discloses internal mechanics (tracing supersession chain with trigger/reason/evidence per hop) and output (active choice). However, it does not explicitly declare the tool as read-only or mention any side effects, auth needs, or rate limits. Basic transparency but lacks safety disclosure.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Two sentences, zero wasted words. Front-loaded with primary purpose, followed by clear usage examples. Efficient communication of key information.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's moderate complexity and no output schema, the description adequately covers what the tool does and what it returns (traced chain with details, active choice). It provides usage examples. Minor gap: lacks details on return format or pagination, but overall sufficient for agent decision-making.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100% for both parameters. Description rephrases the query parameter as 'substring of the decision to explain', which adds little beyond the schema's description. Session_id is not elaborated. Baseline score of 3 is appropriate as description does not significantly enhance parameter understanding.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  Description clearly defines the tool as reasoning over decision history with specific verb 'reason' and resource 'decision history'. It explains the supersession chain tracing and active choice reporting, distinguishing it from sibling tools like analyze_file or checkpoint_session which serve different purposes.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  Provides explicit when-to-use guidance with example user queries ('why did we pick X', 'what happened to Y', 'what was the previous approach'). Does not mention alternatives or when not to use, but the context is clear and sufficient for an agent to select this tool appropriately.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• resume_sessionA
  4.3/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations, the description carries the behavioral disclosure burden. It describes the output ('compact summary of what was done, decided, and what's pending') and usage recommendation, which is transparent for a read-only retrieval tool.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Two concise sentences cover purpose, content, and usage without waste. Essential information is front-loaded.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with 2 parameters and no output schema, the description fully explains its purpose, output nature, and intended usage. No gaps are apparent.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, so baseline is 3. The description adds no parameter-specific details beyond what the schema already provides (e.g., level token sizes). The 'inject into system prompt' advice is helpful but not parameter-focused.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's function: 'Get the resume context for a previous session' and specifies it returns a compact summary. It distinguishes itself from sibling tools like analyze_file or checkpoint_session by focusing on session resumption.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides explicit context on when to use: 'Inject this into the system prompt when starting a new session on the same project.' It lacks explicit exclusions or alternatives, but the usage context is clear.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• analyze_fileA
  4.4/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  No annotations provided, so the description carries full burden. It discloses the tool's token efficiency (~300-500 tokens) and what the summary includes (schema, statistics, sample data). No contradiction detected.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Two sentences, front-loaded with purpose and benefit, no redundancy. Every sentence earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with 3 parameters and no output schema, the description adequately explains the return format (schema, statistics, sample data) and token efficiency. Minor gap: no mention of error handling or prerequisites.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, but the description adds value by explaining the 'query' parameter improves relevance and the 'token_budget' parameter is for max tokens. This goes beyond the schema's bare descriptions.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses a specific verb 'analyze' with a resource 'large file' and lists supported file types (CSV, Excel, PDF, JSON). The sibling tools are unrelated, so differentiation is clear.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description explicitly states a use case: 'Instead of pasting thousands of rows into the chat, use this...' It implies when to use but does not explicitly state when not to use or list alternatives.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.