Server Quality Checklist

Tool Scores

• mymemory_searchA
  4.2/5.0
  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. It discloses that matching is case-insensitive, substring-based, limited to active entries (not inactive/deleted), and searches both text and kind fields. It also states the return shape ({ query, count, matches }). This is solid behavioral disclosure for a read/search tool, though it doesn't mention pagination or match limits which could matter for large vaults.

  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. Every clause adds value: scope (user's vault), function (search for word/phrase), match semantics (case-insensitive substring), search surface (text and kind), filter (active entries), and return shape. Perfectly front-loaded with the most important info first.

  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 1-parameter read tool with 100% schema coverage and clear return description, this is nearly complete. The only gap is no mention of result limits or pagination behavior for large match sets, and no explicit output schema. But given the tool's simplicity, the description is adequate to allow correct invocation. Minor deduction for the missing result-limit detail.

  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% - the single query parameter is fully documented in the schema with description and examples. The description adds the case-insensitive substring detail and the scope (active entries, text and kind fields), which enhances the schema. This lands the baseline at 3 since the schema already does the heavy lifting, and the description adds modest enrichment.

  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 uses specific verb+resource: 'Search the user's MyMemory vault for a word or phrase.' It clearly states the matching behavior (case-insensitive substring) and scope ('active entries (text and kind)'). This distinguishes it from siblings mymemory_get_context and mymemory_propose, which presumably retrieve context or propose additions rather than search.

  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 explains the matching semantics (case-insensitive substring over active entries, both text and kind fields) which gives clear context on what the search will return. It doesn't explicitly state when NOT to use it or name alternatives, but the scope restriction to 'active entries' and the clear verb distinguishes usage from siblings. Slight deduction for no explicit exclusion guidance.

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

• mymemory_proposeA
  4.3/5.0
  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 effectively discloses that entries go to a PENDING queue, that nothing activates without human approval, that there's a max of 20 per call, and that the server dedupes. This is strong behavioral transparency for a write tool with no annotation support.

  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 cohesive paragraph that front-loads the core purpose, then layers in constraints in logical order — durable-only scope, kind taxonomy, limits, dedupe behavior. Every sentence earns its place, with no wasted words or redundancy.

  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 single-parameter write tool with no output schema, the description covers the essential usage context well: what to propose, what not to propose, the kinds, limits, and review flow. The only minor gap is that it doesn't specify return confirmation behavior, but this is less critical given no output schema is expected.

  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 description coverage is 0%, so the description must compensate for the undocumented 'entries' parameter. It does by explaining what kinds are available (directive, fact, preference, note with examples for directive) and explaining the dedupe and pending-queue behavior. The description adds meaning beyond the bare schema, though it doesn't detail the text length constraints or per-kind examples exhaustively.

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

  Purpose4/5

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

  The description clearly states what the tool does: propose new entries to the user's MyMemory vault with a specific verb ('propose') and resource ('MyMemory vault'). It distinguishes from siblings by clarifying this is about writing new durable knowledge, while get_context and search are likely read operations. However, it doesn't explicitly contrast against the siblings, so it's clear but not fully differentiated within the sibling set.

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

  Usage Guidelines5/5

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

  The description provides explicit when-to-use guidance ('when you learn something durable about them'), what NOT to propose ('never one-off task details or things already in the vault'), and the kinds taxonomy. It also explains the pending-queue approval model. This is exemplary usage guidance, clearly stating scope and exclusions.

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

• mymemory_get_contextA
  4.6/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries full burden. It discloses the content structure (context_block format, directives-first ordering) which is genuinely useful behavioral info. It doesn't mention authentication requirements, pagination, or failure modes, but for a zero-parameter read-only fetch tool the disclosure is reasonably complete for what's exposed.

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

  Conciseness4/5

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

  Two sentences, front-loaded with purpose then structure then usage guidance. Slightly dense single paragraph but every clause earns its place. Could optionally be split into bullet points but it's efficient as written.

  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?

  A zero-parameter, no-output-schema tool with clear READ semantics. The description covers what it returns, the internal structure, when to call it, and what to do with the result. For a simple fetch tool this is fully complete — nothing meaningful is left unexplained.

  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 0 parameters and schema coverage is 100%, making parameter semantics a non-issue. The dimension baseline for 0 params is 4, and the description adds context about what behavior to expect without parameters (returns full context).

  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?

  Clear verb (Fetch) + specific resource (user's MyMemory vault context) with detailed description of what's returned (compiled context_block with directives/facts/preferences/notes structure plus raw active entries). Distinguishes well from siblings: get_context returns the full compiled context while search/propose 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 Guidelines5/5

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

  Explicitly states 'Call once at conversation start and apply it' — gives a precise trigger condition. The description's ending ('these are the user's standing rules, facts, and preferences across every AI tool they use') explains why this tool matters and implies it should be prioritized early, which differentiates it from alternative sibling tools.

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