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

With no annotations, the description carries the full burden. It does disclose a key behavioral trait—exact-name lookup returning details or null on miss—which implies read-only and non-exhaustive matching, but says nothing about matching semantics (case sensitivity, fuzzy vs exact, ambiguity handling) or auth.

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

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

Two sentences, zero filler, with the action and the return behavior both front-loaded.

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

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

For a simple single-parameter read with no output schema, stating 'returns entity details or null' covers the essential contract. However, the vague tool name 'entity' and the unresolved question of how this differs from sibling retrieval tools leave real gaps for an agent choosing a tool.

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

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

Schema coverage is 100% and there is only one parameter already documented as 'Entity name or alias to look up'. The description echoes 'name or alias' without adding format or resolution rules, so baseline 3 applies.

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

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

States a specific verb plus resource ('Look up an entity') and even enumerates what counts as an entity (person, project, concept). It does not differentiate from sibling tools like search or facts, so an agent can't tell from the description alone which lookup path to take.

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

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

No indication of when to use this versus 'search', 'facts', or 'keyword', which all plausibly retrieve related information. The only implied usage is 'you have a name', which is thin.

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

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

No annotations exist, so the description carries the full burden and does: it discloses that totals are never computed (the caller must count/sum), recommends preferring items whose dates match the question window, explains cache replay at zero model cost for identical questions, and documents the RENOR_EVIDENCE_MODE gating plus the `force` escape hatch. That is unusually rich behavioral context for a tool with zero structured metadata.

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

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

Five dense sentences, front-loaded with the core behavior before the usage guidance, the counting caveat, and the gating mechanics. Every sentence carries actionable information with no filler or restatement of the name.

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

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

With no annotations and no output schema, the description still covers what is returned (distinct items/events/amounts with dates), what is deliberately not returned (no computed totals), how caching affects repeated calls, and how the mode gate behaves. An agent has everything needed to call it correctly and interpret the result.

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

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

Schema description coverage is 100%, so all three parameters are already documented with types and defaults. The description adds narrative meaning to `force` (run even when auto declines) but says nothing about `topK` or how it interacts with the second enumeration pass, so it only marginally exceeds the schema baseline.

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

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

States a specific verb and resource ("Question-conditioned evidence extraction") and concretely describes the two-pass behavior: retrieval followed by enumeration of distinct items/events/amounts with dates. It also names the sibling it overlaps with ("Retrieves like search") and pins down the question class it is for, so an agent can distinguish it from `search` without opening a schema.

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

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

"Best for how-many / how-much / count / list / aggregate questions about the user's history" gives an explicit when-to-use condition, and the gating note plus `force: true` tells the agent how to override a declined call. It stops short of explicitly saying which sibling to use instead for non-aggregate lookups, leaving that inference to the reader.

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

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

With no annotations, the description carries the full behavioral burden. It does disclose the key default: current facts only, with `includeHistory` needed for superseded facts and `asOf` for point-in-time reads. It says nothing about permissions, empty/missing entity behavior, result shape, or volume/pagination for a tool that returns 'All' facts.

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

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

Three short clauses, front-loaded with purpose before the routing hint and the temporal hints. The final clause is telegraphic ('asOf / includeHistory for temporal reads') and slightly fragments the prose, but nothing is wasted.

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

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

For a zero-required-param read tool with a fully documented schema and no output schema, the essentials are present: default scope, history toggle, temporal read. It is not complete on what an entity identifier collision or a nonexistent entity yields, which matters given three interchangeable alias fields.

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

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

Schema coverage is 100%, so all four parameters are already documented, including that asOf is an ISO timestamp and includeHistory means superseded facts. The description's 'asOf / includeHistory for temporal reads' restates the schema rather than adding format, precedence, or interaction rules between the two. Baseline 3 is appropriate.

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

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

States a concrete resource and scope: 'All current lifecycle facts for an entity', and clarifies the entity identifier aliases (name/entityName/subject). It is distinguishable from sibling `search` and, by implication, from `remember_fact` since this reads rather than writes. It stops short of a crisp verb-resource framing (there is no explicit verb).

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

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

Explicitly routes the agent: 'Prefer search for a natural-language question', which is exactly the sibling disambiguation an agent needs. It gives no guidance against `entity`, `evidence`, or `keyword`, and doesn't state what happens if the entity is unknown, so it falls short of a full when/when-not map.

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

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

With no annotations, the description carries the full burden and does substantial work: it discloses that operators are inert, that hyphens are quoted server-side, and that unmatched terms fall back to note paths/frontmatter with a 'note-identity' reason. It omits result ordering/ranking and any indication of cost or latency.

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

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

The key differentiator 'Exact keyword/BM25 search only' is front-loaded and the sentences are dense with useful information. The trailing '(reason: "note-identity")' is an internal artifact that costs clarity more than it earns.

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

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

For a two-parameter, no-annotation, no-output-schema tool, the description covers matching semantics, operator behavior, and fallback resolution adequately. Ranking/ordering of matches and the meaning of topK relative to the fallback path are the remaining gaps.

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

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

Schema description coverage is 100% and the `query` semantics (exact phrase, operators treated as plain words) are already stated in the schema, so the description mostly restates it. It adds only marginal value by explaining the path/frontmatter fallback for unmatched terms; `topK` behavior is not elaborated beyond the schema.

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

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

The description opens with a concrete verb+mechanism ('Exact keyword/BM25 search only'), states the matching rule, and explicitly frames itself against the sibling `search`, so an agent can distinguish the two without opening either schema.

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

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

It gives an explicit routing rule ('Use search for identity and natural-language questions'), which tells the agent when to prefer the alternative. It stops short of covering the other siblings (evidence, entity, note) or stating an explicit when-not condition for this tool.

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

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

With no annotations, the description carries the full disclosure burden and does communicate the key trait that this is additive (append, not overwrite). It omits whether a missing note file is created, whether repeated calls duplicate text, and any auth or rate-limit context.

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

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

Two short sentences, front-loaded with the action. There is mild redundancy between 'Store a memory entry in the daily notes' and 'Appends text to the daily note', but nothing extraneous follows.

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

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

An output schema exists, so return values need not be explained, and all three parameters are documented in-schema. Still, for a mutation tool with zero annotations, the description should state side effects such as note creation and duplicate handling; its absence leaves a real gap.

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

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

Schema description coverage is 100% and the schema already explains the date format, default-to-today behavior, and the unusual ignored 'source' parameter. The description only echoes 'given date' and adds nothing beyond the schema, so the baseline 3 applies.

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

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

The description states a specific verb and resource: it appends text to the daily note for a given date. That is clearly distinct from a generic write, but it never distinguishes this append-a-journal-entry behavior from siblings like remember_fact or facts, which serve overlapping memory-storage purposes.

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

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

There is no guidance on when to use this tool instead of remember_fact, entity, or evidence, and no exclusions. An agent choosing among six memory-related siblings gets no routing signal.

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

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses ledger-first durability, temporal supersession that closes the previous current fact, that it returns a receipt, and that confidence is not representable. It does not cover permissions, rate limits, or exact reversal behavior, which prevents a top score.

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

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

The description is compact and front-loaded: it begins with the core operation, then layers in durability, temporal behavior, return behavior, and usage trigger. Every sentence adds information without repetition.

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

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

An output schema exists, so omitting receipt details is acceptable, and the description sufficiently explains the write model, supersession, and usage trigger. It leaves some operational context unexplained, such as authorization or duplicate-handling nuances, but is complete enough to call correctly.

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

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

Schema description coverage is 100%, so the parameter fields are already fully documented by the schema. The description adds useful semantics around subject+predicate temporal supersession and the fact that confidence cannot be stored, but it does not add syntax or format detail beyond the schema.

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

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

The description states a specific verb and resource: a durable memory write that stores or supersedes a fact about a subject. It distinguishes itself from read-oriented siblings like facts and search by framing the operation as a write, though it does not explicitly name the sibling alternatives.

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

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

It gives a clear trigger phrase, 'Use for "remember that…" statements,' which helps the agent recognize when to invoke it. It does not explicitly state when not to use it or compare it with sibling tools such as note or evidence.

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

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

With no annotations, the description carries the burden and does disclose real behavior: output ordering (matching lifecycle facts first, then chunks), per-hit session_date with a required rendering template, a no-rewrite constraint on chunk text, and the conditional evidence second pass with its 12-note/6k cap and caching. It omits latency, permissions, and failure behavior, but the return shape is unusually well specified.

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

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

The purpose is front-loaded, but the body drifts into implementation detail — RENOR_SEARCH_EVIDENCE, 'H10-v4 evidence second pass', '12-note/6k cap' — which is internal jargon an agent cannot act on. It also mixes formatting instructions into the same run-on block rather than separating routing from output handling.

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

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

For a 2-parameter, annotation-free, no-output-schema tool, this covers purpose, sibling routing, result composition, and mandatory rendering conventions — enough to call and consume it correctly. The gaps are around comparisons to the remaining search siblings rather than missing mechanics.

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

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

Schema coverage is 100%, so both query and topK are already documented with type and range. The description implies the query style (natural-language who/what/where questions) but adds no format, syntax, or topK tuning guidance beyond the schema baseline.

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

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

Opens with a specific role statement — the DEFAULT retrieval tool for questions about the user or the vault, scoped to identity/preference/project questions — and clarifies it returns lifecycle facts plus semantic chunks. It distinguishes itself from keyword search and from remember_fact, though it says nothing about how it differs from the evidence, entity, or facts siblings.

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

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

Explicit routing guidance: use this first for identity questions, do not start with keyword search, and send durable writes to remember_fact. It lacks exclusions or comparisons against evidence/entity/facts, which are the closest remaining alternatives, so it stops short of full when/when-not coverage.

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

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

No annotations are provided, so the description carries the behavioral disclosure burden. 'Get' implies a read-only operation, and the description names the categories of statistics returned, but it does not explicitly confirm safety, freshness, caching, permissions, or side-effect behavior.

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

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

The description is a single front-loaded sentence with no filler. The verb and resource come first, followed by the specific statistics available.

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

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

For a zero-parameter status tool with an output schema, the description provides enough context to understand what the tool returns. Return-value formatting is covered by the output schema, so the description need not repeat it.

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

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

The schema has zero parameters, so there is nothing for the description to clarify at the parameter level. The baseline for a parameterless tool is therefore appropriate.

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

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

The description gives a specific verb and resource: 'Get vault index statistics,' and enumerates the exact counts returned (notes, chunks, entities, facts, relations). This clearly distinguishes it from sibling tools like entity, facts, keyword, and search, which deal with records or searching rather than index-level statistics.

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

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

Usage is implied by the tool name and the statistics-oriented description: an agent can infer it is for inspecting index size/contents. However, the description does not explicitly state when to use this tool versus alternatives such as search or facts, nor does it mention any prerequisites or exclusions.

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