CueMap MCP Server

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

With no annotations provided, the description must disclose behavioral traits on its own. It mentions that the tool creates a project when needed and applies deterministic cue extraction, but it does not describe return values, error handling, idempotency, or the effect of async_ingest. This is insufficient for a mutation tool.

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 sentence that efficiently packs the main purpose and a few behavioral details. It is appropriately concise and front-loaded with the core action, though it could be split for readability.

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?

Given the tool's complexity (9 parameters, nested metadata, no output schema) and the presence of sibling tools, the description is incomplete. It does not explain the return value, when to use this vs. ingest tools, or the significance of async_ingest and disable_temporal_chunking. An agent would lack critical context for correct invocation.

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 baseline is 3. The description adds some context about cues and metadata ('applies deterministic cue extraction plus any cues and metadata'), which clarifies their role, but it does not elaborate on other parameters like async_ingest or source_key. It adds marginal value 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 clearly states the action ('Store a natural-language memory in CueMap') with a specific verb and resource. However, it does not differentiate from sibling ingestion tools like cuemap_ingest_content, which also store content, so it falls short of the top score.

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?

The description provides no guidance on when to use this tool versus alternatives such as cuemap_ingest_content, cuemap_ingest_url, or cuemap_recall. It mentions the default project behavior but not when this tool is preferred.

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 full burden for behavioral disclosure. It states that a mapping is added, but not whether re-adding an existing pair overwrites, errors, or merges, nor any side effects on recall, classification, or project state.

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?

A single front-loaded sentence with no wasted words. 'Manual' and 'weighted' carry semantic load that helps distinguish this from related alias operations.

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 mutation tool with no annotations and no output schema, the description is too thin. It does not explain duplicate handling, return values, or how the mapping interacts with project scoping beyond what the schema already specifies.

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 leaves 'from' and 'to' undocumented except for minLength, and the description fills that gap by clarifying they are 'one cue to another'. This adds semantic meaning beyond the schema, while 'weight' and 'project' already have schema descriptions.

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 'Add' and resource 'manual weighted mapping from one cue to another'. This distinguishes it from siblings like cuemap_alias_merge (merge vs add) and cuemap_intent_classify (manual vs automatic).

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 explicit guidance on when to use this tool versus cuemap_alias_merge, cuemap_alias_list, or cuemap_add. The word 'manual' implies a contrast with automatic processes, but no alternative or exclusion conditions are stated.

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 must carry the behavioral burden. 'List' clearly signals a read-only operation, but the description does not clarify what 'manual' aliases are versus other alias kinds, whether results are affected by project scope, or what the returned data looks like. These gaps are material in the absence of an output schema.

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 one tightly written sentence with no filler or duplicated schema information. The core action and scope are front-loaded before any optional detail would be needed.

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 list tool this is not badly incomplete, but the absence of annotations and output schema raises the burden: it does not describe return values, empty results, or how project scoping affects manual aliases. Enough for basic invocation, not enough for confident handling of edge cases.

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 only 50%: 'project' is documented, but 'cue' is not. The description helps by stating aliases are 'associated with one cue,' but it does not explain the cue value format or how the optional project parameter interacts with the listing. It adds modest meaning without compensating fully for the undocumented parameter.

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 uses a specific verb ('List'), identifies the resource ('manual cue aliases'), and scopes it to 'one cue', which distinguishes it from sibling alias mutators like cuemap_alias_add and cuemap_alias_merge. An agent can tell what this tool does without opening the 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?

The description implies the tool is for retrieving existing aliases for a specific cue, but it does not state when to prefer it over alternatives, mention any preconditions, or give exclusion criteria. The usefulness is inferred from the verb and sibling context rather than stated explicitly.

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 of behavioral disclosure, but it mostly restates the schema's confirmed constraint. It does not disclose whether source cues are removed or altered, whether the merge is reversible, or what side effects occur, leaving important mutation behavior unspecified.

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-load the purpose and then state the confirmation constraint. There is no filler or redundant elaboration.

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 low-complexity merge tool, the description and schema together make it barely callable: required parameters are identifiable and the canonical-cue wording explains the operation. However, the absence of annotations, output schema, side-effect disclosure, and selection guidance leaves meaningful gaps for an agent deciding whether and how to invoke 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?

Schema coverage is 50%, covering project and confirmed but not cues or to. The description partially compensates by implying that 'multiple cues' correspond to the cues parameter and 'one canonical cue' clarifies the to target, though it adds no detail on relationships, formatting, or edge cases.

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 concrete action and resource: 'Merge multiple cues into one canonical cue.' This clearly conveys what the tool does and makes its merge role apparent, but it does not explicitly distinguish itself from sibling alias tools such as cuemap_alias_add or cuemap_alias_list.

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 guidance is given about when to use this tool versus its sibling alternatives, such as adding an alias or listing cues. The only usage-style note is the confirmed parameter rule, which is also present in the schema and does not address tool selection.

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 full burden of behavioral disclosure. It tells the agent the operation persists content, but it does not disclose side effects such as chunking, embedding, deterministic replacement via source_key, default project behavior, or whether repeated ingestion is idempotent. For a write-oriented tool this is a significant 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.

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

The description is two short sentences with the core action front-loaded and no wasted words. It is appropriately concise for an opening summary, but it is also very terse given the complexity of the tool.

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?

This is a complex 12-parameter tool with no output schema and no annotations, yet the description only covers the basic trigger. It omits guidance on how raw content is processed, how source_key influences replacement, when to provide structural_cues, and what happens after ingestion. An agent would be unable to make informed decisions about most optional parameters.

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 only 42%, and the description adds no parameter-level meaning. It restates the content input but says nothing about segmenter choices, segment window sizes, metadata shape, structural_cues, or source_key semantics. The description does not compensate for the low schema coverage.

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 ('ingest'), a specific resource ('supplied raw content' into CueMap), and a precise trigger ('when the user asks to persist'). It distinguishes itself from siblings like cuemap_ingest_url and cuemap_ingest_file by emphasizing raw content rather than URL/file input.

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?

The description gives an explicit when-to-use rule: 'Use only when the user asks to persist that content.' This is an effective gate that prevents casual or speculative invocation, though it does not explicitly name alternative tools or explain when to prefer cuemap_add versus 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?

No annotations are provided, so the description carries full responsibility. It only says 'Explicitly ingest' – no mention of side effects, idempotency, error behavior, or whether existing data is overwritten. For a mutation tool, this is a significant gap.

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, front-loaded with the purpose and a clear usage constraint. Zero waste; every word earns its place.

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 2-parameter tool with no output schema, the description covers purpose and usage. However, as a mutation tool with no annotations, it lacks behavioral context (e.g., what happens on duplicate ingest, whether it's reversible). This is a moderate gap for an agent relying solely on the description.

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%, with both 'path' and 'project' having clear descriptions. The tool description adds no parameter-level detail, but the schema already documents them adequately. Baseline of 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?

The description clearly states 'Explicitly ingest one local file into CueMap' – a specific verb and resource. The phrase 'local file' distinguishes it from sibling tools cuemap_ingest_url and cuemap_ingest_content. However, it doesn't name those siblings explicitly, so a slight deduction for not reinforcing the distinction.

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?

'Use only for a file the user has placed in scope and asked to ingest' gives a clear condition for use and implies it's not for URLs or content. It doesn't explicitly mention alternatives, but the condition is unambiguous enough 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.

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

With no annotations provided, the description carries the full disclosure burden. It does add one genuine behavioral trait beyond the schema — 'optionally crawling same-domain links' — which reveals recursive behavior. However, it does not disclose side effects such as persistent writes to project knowledge state, prerequisites, or the time/cost implications of deep crawls.

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 tight sentences with zero filler: the action is front-loaded ('Explicitly ingest content from a URL') and the usage gate follows immediately. Every clause earns its place, and 'Explicitly' usefully signals that this is a deliberate, user-triggered action rather than an automatic side effect.

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 tool with no annotations and no output schema, the description covers the core purpose, the optional crawl behavior, and the trigger condition, but omits what the agent should expect after invoking it — such as whether ingested content is persisted into the active project, whether a project must be loaded first, or warnings about slow deep-crawl runs. Adequate but with clear operational 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 75%, and the depth, project, and same_domain_only parameters are already well-described in the schema itself; the url parameter is self-evident from the tool's purpose. The phrase 'crawling same-domain links' faintly reinforces the depth/same_domain_only semantics but adds no new parameter-level detail beyond what the schema provides.

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: 'Explicitly ingest content from a URL.' The URL source clearly differentiates this tool from its ingest siblings (cuemap_ingest_content, cuemap_ingest_file), though it does so implicitly by naming the resource rather than explicitly naming the 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?

The second sentence provides an explicit usage gate: 'Use only when the user asks to ingest that URL.' This gives a clear when-condition but stops short of a 5 because it does not name alternatives or when-not-to-use cases, leaving the agent to infer the boundary between this and the other ingest tools.

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 provided, the description carries the full disclosure burden. It does reveal significant behaviors: the operation applies a state-changing scope and starts a persistent filesystem watcher, and it is gated on explicit user confirmation. However, it does not disclose what happens on re-invocation (overwrite vs. no-op), whether the watcher runs indefinitely or how it is stopped, or the effect on existing CueMap data for the repository.

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 with zero filler. The core action and its dual nature (apply scope + start watcher) are front-loaded in sentence one, and the critical safety protocol is delivered compactly in sentence two. Every sentence earns its place.

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?

Given six parameters, zero annotations, and no output schema, the description covers the most critical context — the preview-then-confirm gate — which mitigates the biggest misuse risk. But it omits other necessary operational details: what the call returns, behavior when invoked twice on the same repository, failure modes when the preview was skipped, and watcher lifecycle management.

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 the baseline of 3 applies. The description adds marginal meaning by tying the 'confirmed' parameter to the explicit user-confirmation workflow ('before setting confirmed=true'), which is genuinely useful. But it adds nothing beyond the schema for path, projectName, includedPaths, ignoredPatterns, or ignoredExtensions.

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 uses specific verbs ('apply', 'start') tied to concrete resources ('ingestion scope', 'incremental filesystem watcher'), clearly stating both what the tool does and that it is the confirmation-gated finalization step. It also distinguishes itself from the sibling cuemap_init_preview by framing preview as the preceding step, so an agent can select it correctly without opening schemas.

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 explicit sequencing guidance: 'Always call cuemap_init_preview first for a new repository and obtain explicit user confirmation before setting confirmed=true.' This names the key alternative (preview) and the condition that selects it. However, it provides no when-not-to-use guidance or fallback alternatives against the other 30 siblings, so it stops short of full exclusion semantics.

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 provided, the description carries the full burden of behavioral disclosure. It explains that the tool does not ingest content and that it produces grouped paths for user review, which are both meaningful behavioral traits. It could add more detail about return structure or side-effect guarantees, but the core non-ingesting behavior is clearly disclosed.

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 two sentences with no filler. The first sentence front-loads the purpose and key non-ingesting behavior, and the second provides actionable workflow instructions. Every sentence earns its place.

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 tool with no output schema and no annotations, the description gives enough information to understand when to call it, what it does, and how to use the result, namely presenting grouped paths to the user. It does not specify the exact format of the grouped paths, but the workflow guidance compensates for that 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?

The input schema already describes all five parameters with 100% coverage, so the description does not need to add parameter details. The description only indirectly references selection adjustment via includedPaths and ignoredPatterns, but it does not meaningfully enhance the schema-provided semantics.

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 action, 'Preview supported repository files', and a key behavioral qualifier, 'without ingesting content'. It clearly distinguishes this tool from cuemap_init and the ingestion tools by positioning it as the pre-initialization preview step.

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?

The description explicitly says to call this before first-time repository initialization and before calling cuemap_init, and gives a clear workflow: present the grouped paths to the user and ask for confirmation or adjustment. It does not explicitly state when not to use it, but the timing and workflow are unambiguous.

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 of behavioral disclosure. It adds a useful caveat that 'scores are ranking signals, not calibrated probabilities,' which prevents misinterpretation of the output, but it does not disclose side effects, local-processing implications, or any limits that might affect invocation.

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 concise sentences, with the core action front-loaded and the important score-interpretation caveat placed second. Every word earns its place and there is no redundant filler.

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?

There is no output schema and no annotation, so the description is the only source of return-value information. It mentions 'recall/memory eligibility signals' but does not explain the shape of the response, how scores map to eligibility, or how the 'target' parameter changes the behavior, leaving an agent under-informed for a classification 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 67%, so two of three parameters already have descriptions. The tool description adds context around 'recall/memory eligibility signals' which helps clarify the 'target' enum, but it does not describe the text, target, or project parameters directly or add format-level meaning 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 action ('Classify text with CueMap's local intent model') and a clear deliverable ('return recall/memory eligibility signals'). It distinguishes the tool as an intent-classification step rather than a storage or retrieval operation, though it does not explicitly name any sibling it is not.

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 when-to-use or when-not-to-use guidance is provided. The description does not compare this tool to sibling tools such as cuemap_recall, cuemap_memory_get, or the ingest tools, leaving the agent to infer when classification is the appropriate step.

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 safety burden and clearly discloses that deletion is permanent, plus the confirmation gate. It could add side-effect details, but the core destructive behavior is explicit.

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 with no filler: purpose first, safety condition second. Every word is functional.

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 low-complexity destructive operation, it covers the essential purpose and the confirmation requirement that prevents accidental deletion. With no output schema, it does not describe return values or not-found behavior, but those are less critical than the irreversible-action guard, which is present.

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 already describes project and confirmed; the description reinforces the confirmed guard. However, entry_id has no schema description and the tool description only implies it identifies 'one Lexicon entry', leaving the accepted ID formats/format semantics to inference.

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 specific verb 'Permanently delete' and resource 'one Lexicon entry', making the operation unmistakable. It is clearly distinct from sibling tools like cuemap_lexicon_inspect or cuemap_memory_delete.

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?

Clear context: this is the tool for permanently deleting a single lexicon entry, and it adds an explicit safety rule for setting confirmed=true only after user confirmation. It does not enumerate when-not-to-use alternatives, but no delete-specific sibling competes with this operation.

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 provided, the description carries the full safety burden; 'Read' does convey that this is a non-mutating operation. However, it does not state what the returned graph looks like, whether it can fail for missing or uninitialized lexicons, or any other behavioral 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?

The description is a single, front-loaded sentence with no filler or repetition. Every word adds value, which is appropriate for a simple one-parameter read operation.

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?

Given the low complexity and full schema coverage, the description plus schema are enough to invoke the tool correctly. But because there is no output schema and no mention of how the graph relates to cuemap_lexicon_inspect or when the graph is unavailable, the definition is merely adequate rather than complete.

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 only parameter, 'project', already has a clear description including its default behavior. The tool description adds no additional parameter-level meaning, so the baseline score of 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?

The description names a specific verb ('Read'), a specific resource ('current Lexicon graph'), and the scope ('for a project'), so an agent can infer the basic operation. It does not, however, differentiate this from sibling tools like cuemap_lexicon_inspect or cuemap_lexicon_wire, so it is clear but not fully distinguishing.

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 call this tool instead of siblings such as cuemap_lexicon_inspect or cuemap_recall, and no conditions or exclusions are stated. The only context is the optional project parameter in the schema; the description itself provides no decision rules for selecting between tools.

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 of behavioral disclosure. The verb 'Inspect' strongly implies a read-only, non-mutating operation, and it names what is being examined. However, it does not explicitly state that nothing is modified, what happens when the cue is absent, or what form the inspection results take.

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 concise sentence that front-loads the action and object. Every word contributes to understanding the tool's purpose, with no filler or 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?

There is no output schema, so the description should clarify what an agent can expect from the inspection, but it only mentions 'relationships' without detail. It also lacks any mention of error conditions, permission needs, or relationship to sibling lexicon operations, leaving important operational context unspecified.

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 50%: the optional 'project' parameter is already described in the schema, while 'cue' has no description. The tool description reinforces that 'one cue' is the target but adds no format, encoding, or cue-identity details. Given the simplicity of the parameters, this is adequate but not enriching.

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 uses the specific verb 'Inspect' and identifies a single resource ('one cue') plus the relationship domain ('Lexicon relationships'). It is clear about the tool's core action and scope. It does not explicitly distinguish itself from siblings like cuemap_lexicon_graph or cuemap_lexicon_wire, so it stops short of a 5.

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?

The description provides no guidance on when to use this tool versus alternatives such as cuemap_lexicon_graph, cuemap_lexicon_wire, or cuemap_recall. There are no stated conditions, exclusions, or context cues that would help an agent choose between closely related lexicon tools.

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 full burden. It implies a manual mutation operation but does not disclose side effects, permissions, or behavior on existing mappings. It fails to explain what happens when the token already exists or whether the operation is reversible.

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 that states the core action immediately. It is concise and free of filler, though it may be too terse to convey necessary context.

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 tool with 3 parameters, no output schema, and no annotations, the description is severely incomplete. It omits return values, prerequisites, edge cases, and operational details, making it inadequate 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.

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

Schema description coverage is only 33%, with only 'project' described. The description does not elaborate on the meaning or expected format of 'token' and 'canonical', leaving critical parameters undocumented. It adds little beyond the parameter names themselves.

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 clearly states the action ('wire') and the resource ('token to a canonical Lexicon cue'), distinguishing it from sibling tools like cuemap_lexicon_delete or cuemap_lexicon_inspect. However, 'wire' is somewhat ambiguous and could be more explicit about the mapping action.

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 versus alternatives such as cuemap_alias_add or cuemap_add. No conditions, prerequisites, or exclusions are mentioned.

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?

The description discloses the permanent, destructive nature of the operation and the requirement for explicit confirmation, which are the most critical behavioral traits for a delete tool. Since no annotations are provided, the description carries the full burden; it covers the key safety aspect but does not mention side effects, prerequisites, or response 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, direct sentence that front-loads the primary action and then adds the critical confirmation constraint. There is no wasted wording, and the structure is optimally concise.

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 destructive delete operation, the description covers the essential action and the confirmation gate, but it omits any details about the memory_id semantics, potential side effects, or the response. Given that the schema also lacks a description for memory_id, an agent might not know how to specify which memory to delete. The description is minimally adequate but not fully complete.

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 description repeats the confirmed parameter's condition that is already stated in the schema ('Must be true only after explicit user confirmation'), adding no new meaning. It does not describe the memory_id parameter at all, which lacks a schema description. With 67% schema coverage, the description should compensate for the undocumented memory_id but fails to do so.

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 clearly states the action: 'Permanently delete one CueMap memory.' It uses a specific verb and resource, and the word 'one' distinguishes it from any batch or bulk operations. It is also immediately differentiable from sibling tools like cuemap_memory_get and cuemap_memory_reinforce.

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?

The description provides no explicit guidance on when to use this tool versus alternatives. The only usage-related note, 'Set confirmed=true only after explicit user confirmation,' is a parameter-level instruction rather than tool-selection guidance. Usage is implied by the delete action, but no alternatives or exclusions are mentioned.

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 must carry the behavioral burden. It does so well by disclosing the read-only nature ('readable text'), the inclusion of source metadata, and two explicit operational limits: 'Does not expand neighbors or read live source files.' This gives an agent useful behavioral expectations 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.

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

Three short sentences, each earning its place: the first defines the action and output, the second explains parameter provenance, and the third states limitations. There is no fluff or repetitive content.

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?

Given the low complexity of a two-parameter read operation, the description is complete enough. It covers what the tool does, what it returns, where the parameters come from, and what it deliberately avoids doing. Without an output schema or annotations, this description provides sufficient context for correct invocation.

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 50% because only project has a description. The description compensates by explaining that memory_id and project should come from recall results, clarifying their relationship and intended source. This adds meaning beyond just the parameter names and types.

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: 'Get one stored memory as readable text with source metadata.' It clearly differentiates this from sibling memory tools like cuemap_memory_delete or cuemap_recall by focusing on single retrieval with metadata and explicitly saying it does not expand neighbors or read live source files.

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?

The description gives a clear instruction on when to use it: pass the memory_id and owning project_id from recall. It implies the workflow of first using recall to obtain IDs, then calling this tool. It does not explicitly name alternative tools or exclusions, but the 'from recall' context is sufficient guidance.

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 is the only source of behavioral information. It reveals that the operation targets one memory and can follow specific cue pathways, but it does not state whether the operation mutates stored memory, whether it is idempotent, or what side effects or failures may occur.

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?

One sentence with no filler or repetition; the key action and scope are front-loaded. It is efficiently written, though the brevity contributes to ambiguity that is penalized in other dimensions.

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 tool with no annotations and no output schema, the description is too thin: it omits return value, side effects, and any guidance on required versus optional inputs beyond the schema. An agent cannot tell what 'reinforce' will actually do or what a successful call returns.

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 low (33%); only `project` has a description. The phrase 'along specific cue pathways' clarifies that `cues` selects pathways, and `memory_id` is inferable, but the description does not explain the exact semantics or constraints for the cues array or the effect of omitting it.

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?

Uses a specific verb ('reinforce') and resource ('one CueMap memory'), and the optional 'cue pathways' qualifier gives it a recognizable scope. It is distinguishable from siblings like cuemap_memory_get/delete, though 'reinforce' is domain jargon and not precisely defined.

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 when-to-use, prerequisites, or alternatives are mentioned; the description only states the action. The intended context must be inferred from the tool name and sibling set, so guidance is effectively absent.

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 provided, the description carries the burden of behavioral disclosure and it explicitly states that the operation does not reload or mutate the project. It does not explain what 'artifact metadata' contains or what side effects may still occur, but the core safety property of this inspection tool is clearly disclosed.

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 sentence that leads with the key verb and object, then adds the critical non-mutation qualifier. There is no redundant phrasing or filler.

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?

The tool has only one optional parameter, and that parameter is documented in the schema. However, with no output schema and no annotations, the description leaves 'CueBridge artifact metadata' vague and does not state what the returned metadata includes or whether the project must already be loaded. That is a meaningful gap for an agent choosing or invoking the 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 description coverage is 100%: the only parameter 'project' is fully described as an optional ID defaulting to the repository-scoped project. The tool description adds no new parameter-level meaning, so the baseline score of 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 uses a specific verb ('Inspect') and a clear resource ('CueBridge artifact metadata for a CueMap project'), and adds a non-reloading/non-mutating qualifier that separates it from mutation-oriented siblings like cuemap_project_save, cuemap_project_push, and cuemap_project_sync. This is enough for an agent to know what the tool does at a glance.

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?

The phrase 'without reloading or mutating it' implies this is the read-only metadata inspection option, but no explicit when-to-use guidance or alternative is named. Sibling names suggest related operations, yet the description does not tell an agent when to choose this over cuemap_project_pack, cuemap_project_export, or cuemap_lexicon_inspect.

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 full burden of behavioral disclosure. It mentions cursor-pagination but says nothing about whether the operation mutates state, what the boolean include_* flags control by default, what the response looks like, or how pagination actually behaves across pages.

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?

A single clear sentence with no wasted words, which is structurally sound. However, it's closer to under-specification than genuine conciseness — the brevity comes at the cost of essential information.

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 tool with 6 parameters, no annotations, no output schema, and 17% schema coverage, this description is inadequate. An agent cannot determine the meaning of the boolean include flags, the pagination mechanics, or the expected return shape without additional investigation.

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 only 17% (only 'project' is documented). The description must compensate for the other five undocumented parameters but doesn't explain limit, cursor, or the include_cues/include_content/include_metadata flags. The word 'cursor-paginated' hints at cursor and limit but provides no syntax or semantics.

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 clear verb (export), resource (memories from a CueMap project), and a key distinguishing feature (cursor-paginated). It's specific enough to convey the basic function, though it doesn't explicitly contrast with siblings like cuemap_project_pack or cuemap_memory_get.

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 guidance on when to use this tool vs alternatives. With 29 siblings including overlapping tools like cuemap_project_pull, cuemap_memory_get, and cuemap_recall, the absence of any routing guidance leaves the agent to infer when this is the right choice.

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 behavioral disclosure burden. It does well by explaining the effect ('load into RAM'), the trigger ('explicit warm-up'), and the default behavior of normal requests ('load automatically'). It omits edge-case details like behavior when the project is already loaded, but this is not a major gap for a warm-up tool.

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, no fluff, and the core purpose is front-loaded. Both the 'what' and the 'when' are communicated efficiently without repeating schema content.

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 low-complexity tool with one optional parameter and no output schema, the description provides enough context to call it correctly. It could mention what happens if the project does not exist or is already loaded, but those are minor omissions given the warm-up framing.

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 already documents the single 'project' parameter with 100% coverage, including its default behavior. The description adds no additional parameter-level detail beyond the schema, so the baseline score of 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?

The description states a specific verb ('Load'), a specific resource ('persisted CueMap project'), and a clear purpose ('before a latency-sensitive operation'). It also differentiates the tool from normal automatic loading by framing it as 'explicit warm-up.'

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?

The description gives clear guidance on when to use this tool: before latency-sensitive operations, and explains that normal project requests do not need it because they load automatically. It does not name sibling alternatives explicitly, but the warm-up context is sufficient for routing.

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 it adds meaningful behavioral context by warning that the package contains sensitive project content and must only be written after explicit user approval of the exact path. It could also mention overwrite/error behavior or return value, but the safety-relevant side effect is clearly disclosed.

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 two dense, purposeful sentences: the first states the action and target artifact, and the second adds the essential human-approval condition. There is no filler or redundant schema text.

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?

Combined with the schema, the definition covers the core action, the output artifact, and the critical approval gate, even without annotations or an output schema. It would be more complete if it distinguished this tool from project_export/save and described overwrite behavior, but nothing essential for correct invocation is missing.

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 schema already documents output_path, project, confirmed, and overwrite. The description adds context that the output is a local .cuemap file and that the path must be exact, but it does not meaningfully explain parameter behavior 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 first sentence uses a specific verb and resource: 'Write a ready-to-query .cuemap package for one project to a local file.' This clearly conveys the core action and scope. It does not explicitly contrast siblings such as cuemap_project_export or cuemap_project_save, so it stops short of a 5.

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?

The description gives a clear safety precondition: use only after explicit user approval of the exact output path. However, it does not say when to choose this tool over the many project-related siblings like export, save, or package_load, nor does it state exclusions.

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 it does add some safety context: 'existing projects are never overwritten' and the requirement for explicit approval. However, it does not explain side effects, return values, or what 'warm' concretely does, leaving notable gaps.

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 communicate the core action, the approval constraint, and the non-overwrite safety guarantee. Every sentence earns its place and the key information is 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?

The description is adequate for selecting and invoking the tool, especially with a complete parameter schema. But because there is no output schema and no annotations, the description should also cover likely side effects and result behavior; it only partially does so.

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 both confirmed and package_path are already documented in the input schema. The description reinforces the approval requirement but adds no new parameter-level meaning 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 clearly states the action ('Install and warm') and the resource ('a local .cuemap package'), which is more specific than the tool name alone. It does not explicitly contrast with siblings like cuemap_project_load, so it is clear but lacks direct differentiation.

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?

The description gives a firm when-to-use condition: only after the user explicitly approves the exact package path. It does not explicitly say when not to use this tool or mention alternatives, so it stops short of full routing guidance.

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 full burden. It discloses key behavior: uses the engine host's AWS CLI, requires explicit approval, and never overwrites existing projects. This goes beyond the schema and gives an agent important safety-relevant 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 compact sentences with no filler. Critical constraints are front-loaded and every clause earns its place.

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 safety-sensitive install operation with no annotations and no output schema, the description is largely complete: it explains the action, source, prerequisite, and non-destructive guarantee. It does not describe response format or what happens after success, but that is a minor gap here.

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%, with both source and confirmed having descriptive meanings. The description reinforces the exact S3 source requirement but adds little parameter-specific detail beyond what the schema already provides.

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 action: download, install, and warm a .cuemap package from an S3 source using AWS CLI. The resource and operation are clear, and this clearly differentiates from sibling tools like push, load, or sync.

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?

Provides a clear prerequisite: use only after explicit approval of the exact S3 source. Does not explicitly name alternatives or when-not-to-use scenarios, but the context is sufficient for an agent to gate invocation.

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 provided, the description carries the full burden. It discloses the destructive overwrite risk, the approval requirement, and the reliance on the host's AWS CLI credentials. This is meaningful behavioral context beyond a simple 'uploads a project' statement.

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 with no redundancy. The first names the action and mechanism; the second delivers the critical safety precondition and risk. Every word adds value.

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 three-parameter tool with no output schema and no annotations, the description covers the essential operational context: what it does, how it does it, and the key risks. It does not describe return values or failure modes, but the absence of an output schema lowers that burden.

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 schema already documents all three parameters. The description adds context about the S3 URI being exact and the approval requirement, but it does not materially extend parameter semantics beyond the schema's own descriptions.

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 action ('Pack and upload a CueMap project') plus the execution mechanism (engine host's configured AWS CLI). This clearly distinguishes it from sibling cuemap_project_pack, which likely only creates a local pack without uploading.

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?

The description gives an explicit precondition: use only after approval of the exact S3 destination. It also warns about the destructive possibility of replacing an existing object. It does not name alternatives or explicitly say when not to use it, but the approval gate is a strong usage guideline.

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 full burden, and it does disclose a useful read-only trait (list operation with no parameters) and a domain-specific detail: it reveals RAM-loaded status. It doesn't mention pagination, ordering, or stale-project nuances, but for a zero-parameter 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.

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

One tight sentence that front-loads the verb and resource. It packs two metadata details without waste; only a note about the loaded-in-RAM indicator could arguably be expanded, but nothing is extraneous.

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 parameterless list tool, the description is mostly complete: it names the resource and output fields. However, it doesn't state typical list semantics (ordering, size, project scope), and there is no output schema to fill that gap. Slightly above minimum.

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 tool has zero parameters, so the description naturally cannot add parameter meaning. The baseline for 0-param tools is 4, and the description correctly frames the tool as a no-argument listing operation.

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 (List), a clear resource (CueMap projects), and two specific bits of metadata (summary info, RAM-loaded status). It clearly distinguishes this list-style tool from load/save/unload 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?

No guidance on when to use this tool vs alternatives. Among many project-related siblings (load, save, unload, status), the description doesn't tell the agent when listing is the right choice or what use case it serves.

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. It clarifies the operation does not unload the project and that it is a durable persistence action, but it does not mention overwrite behavior, failure modes, or side effects.

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 concise sentences with no wasted words. The key fact is front-loaded, and the usage guidance is compact and immediately actionable.

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 one-optional-parameter tool, the description covers what it does and when to use it. There is no output schema or annotation coverage, so some details like return behavior are absent, but the tool is simple enough that the description is largely sufficient.

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 already documents the single parameter at 100% coverage, including its default behavior. The description adds no additional parameter-level meaning beyond what the schema provides, matching the 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: persist the current state of a CueMap project. It also distinguishes itself from operations that unload and notes that package operations save automatically, so an agent can separate it from related 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?

Explicitly says to use this only when an explicit durable checkpoint is useful, and clarifies that package operations already save. It names the general alternative category but not the specific sibling tool, leaving a small gap.

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 of behavioral disclosure. It clearly states the tool pushes local-only changes, pulls remote-only changes, and refuses divergent histories or stale concurrent writes. This covers the important safety-critical behavior of refusing conflicts. It does not mention return values or error formats, but the core mutation behavior and its guardrails are transparent.

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. The primary action is front-loaded, followed by the two key behavioral outcomes and a critical approval precondition. Every clause earns its place, making the description easy to parse quickly.

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 sync tool with 3 parameters, no annotations, and no output schema, the description covers the essential context: what it does, how it behaves on divergence, and the approval precondition mapped to the 'confirmed' parameter. It does not describe the return value or what happens on refusal, but the core decision-relevant information is present. Slightly more detail on outcomes would make it fully complete.

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 schema already documents all three parameters. The description reinforces the meaning of 'remote' as the exact S3 root and 'confirmed' as an approval flag, but it adds no new semantic detail beyond what the schema properties already state. 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?

The description uses a specific verb ('Fast-forward') with a clear resource ('a project through immutable history at an S3 sync root'). It distinguishes itself from sibling tools by explicitly describing the push and pull directions, making it obvious this is a bidirectional sync rather than a one-way push/pull. The purpose is unambiguous.

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?

The description implies usage (when you need to synchronize both local-only and remote-only changes) but does not explicitly name alternatives like cuemap_project_push or cuemap_project_pull or state when to choose this over them. The safety precondition 'Use only after explicit approval' is a condition, not a comparative usage guideline. Therefore usage context is 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.

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 the tool persists the project before unloading, and that active projects cause a retryable busy error. This covers the primary behavioral aspects. However, it does not mention whether the operation is reversible, requires specific permissions, or what happens to the project's state in the repository. Given the lack of annotations, the description provides good but not exhaustive transparency.

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 two sentences, front-loaded with the core action and purpose, followed by a precise usage condition. There is no redundant wording, and every sentence adds value. It is concise and well-structured.

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 tool with one optional parameter and no output schema, the description covers the main action, the error condition, and the usage constraint. It does not explicitly state the success return value, but that is a minor gap given the tool's simplicity. The description is sufficiently 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.

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

The schema description for the 'project' parameter is fully covered (100%) with a clear description including the default behavior. The tool description adds no additional meaning beyond what the schema already provides. Since schema coverage is high, the baseline of 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?

The description clearly states the action (persist and unload) and the resource (CueMap project), with the explicit purpose of reducing memory use. It distinguishes itself from siblings like cuemap_project_load or cuemap_project_save by focusing on unloading from RAM. 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.

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

The description explicitly states when to use the tool: 'Use only when the user explicitly asks to unload or free inactive project memory.' It also provides a behavioral constraint that active projects return a retryable busy error, guiding the agent on when the call will fail. This is direct and actionable usage guidance.

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 mostly meets it: it specifies the return envelope (engine JSON with project_id/memory_id handles, source metadata, diagnostics in text and structuredContent) and the hybrid reranking behavior. It stops short of disclosing side effects such as auto_reinforce altering stored memory state, a notable gap for a tool that can mutate memory.

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?

Four sentences with no filler: purpose, output shape, sibling routing, and operational guidance each get roughly one sentence. The final sentence is slightly dense, packing three separate pieces of advice, 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 30-parameter tool with no output schema and no annotations, the description covers the essentials: what it returns, how to follow up with cuemap_memory_get, and how to start with safe parameter values. Gaps are the auto_reinforce side effect and empty/error behavior, but the core call-and-follow-up flow is complete.

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 the schema already documents all 30 parameters; the description adds cross-cutting guidance beyond it — small limit, depth 1, and enabling reconstruction only when surrounding evidence is needed — which maps onto limit, depth, and the reconstruction/fusion parameters. It does not explain how mode parameters interact, but the baseline is already satisfied by 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?

States a specific verb and resource — 'Recall evidence for a focused question' — and distinguishes itself from the sibling cuemap_memory_get by describing the returned handles and how they are used downstream. The scope (focused recall with follow-up narrowing) is concrete enough that an agent can tell this from ingestion and artifact tools.

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 to cuemap_memory_get when the stored record is needed, naming the key sibling alternative. Operational starting points — 'Start with a small limit and depth 1; enable reconstruction only when surrounding evidence is needed' — give concrete parameter-level guidance. It does not, however, contrast with the wider sibling set (e.g., when to prefer ingestion or intent classification).

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?

There are no annotations, so the description must carry the full behavioral burden. 'Read' suggests a read-only operation, but the description does not disclose whether any side effects occur, whether authentication is required, what statistics are returned, or whether global stats differ behaviorally from project stats.

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 wasted words. It presents the core action first and then defines the scope alternatives.

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 two-parameter read tool, the description conveys the purpose adequately, but with no output schema it should give at least a hint of what statistics are returned. The absence of any return-value information leaves the agent guessing about the tool's output structure.

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 schema already documents 'global' and 'project' clearly. The description adds little beyond restating the project/global scope, so it does not meaningfully elevate the parameter understanding beyond the 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?

The description clearly states the verb ('Read') and resource ('CueMap statistics'), and it specifies the two scopes: repository-scoped project or global engine. It is distinct enough from siblings like cuemap_status or cuemap_projects, though it does not explicitly name a sibling to differentiate from.

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?

The description implies when to use the tool: whenever CueMap statistics are needed, with an option to request global rather than project stats. However, it provides no explicit guidance on when not to use it or which sibling tools might be more appropriate for related needs.

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 provided, the description carries the full behavioral burden. It discloses that the tool reflects background ingestion progress, that it should be polled, and that an idle 0/0 state is not proof of completion. This is meaningful behavioral context, though it doesn't detail potential failure modes or the full status object.

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 two sentences and every sentence earns its place. The core purpose is front-loaded, followed by a crucial usage caveat. There is no redundant or filler content.

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?

Given the tool's low complexity—one optional parameter and no nested objects—the description is largely sufficient. It tells the agent why to call it, when to call it, and what to wait for. The absence of an output schema is partially mitigated by naming verified_complete, though a bit more return-shape context would make it fully complete.

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 only parameter, project, is fully described in the schema with a 100% schema description coverage. The description adds no additional parameter-level meaning, so it meets the baseline of 3 without adding extra value.

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 clearly states the tool's specific function: checking CueMap background ingestion progress for a project. It uses a specific verb and resource, but does not explicitly distinguish itself from sibling tools like cuemap_stats, so it doesn't fully earn a 5.

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?

The description provides explicit guidance on when to use the tool: after cuemap_init, poll until verified_complete is true. It also warns against misinterpreting an initial idle status. However, it does not mention when not to use it or name alternative tools, so it stops short of 5.

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