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

Annotations already carry the safety profile (readOnlyHint=false, destructiveHint=false, non-idempotent), and the description adds the genuinely useful behavioral trait that memories are persistent and shared across agents. It says nothing about expiry semantics, result volume, or what 'recall' returns, which the annotations do not cover.

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, front-loaded with the defining capability followed by the usage instruction. The 'what one agent learns, any agent can recall' clause earns its place by conveying the cross-agent scope that is the tool's whole point.

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 13 parameters fully documented in the schema, no output schema, and annotations carrying safety hints, the description covers the essential read/write duality adequately. It is slightly thin on how the four actions differ in results and on the persistence/expiry model, but nothing critical to 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%, and every parameter is already documented in the schema with per-action hints, so the baseline is 3. The description adds no parameter-level detail (e.g., interplay of query/tags/limit or action-specific parameter usage) 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 names a specific resource (cross-agent persistent memory) and the two core verbs (store, recall), so an agent immediately knows this tool reads and writes shared memory. It does not, however, distinguish itself from closely related siblings such as decision_memory, get_context, or what_should_i_know, so it falls 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?

It gives concrete usage context on both sides: 'store a discovery, decision, or warning' and 'recall prior context before starting work.' That is clear when-to-use guidance, but it offers no exclusions or explicit routing to the sibling memory tools, so it does not reach 5.

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?

Annotations declare readOnlyHint=true, so the safety profile is known. The description adds the behavioral guidance to call before changes, but doesn't disclose return format, rate limits, or what happens if no decisions are recorded. Adds some value beyond annotations but leaves 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 tightly written sentences: first states what it does, second states when to use it. No wasted words, front-loaded purpose.

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 read-only check with fully documented parameters and no output schema, the description covers purpose and timing. It could mention what the check returns (e.g., aligned/misaligned) or how to interpret results, but is largely 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%, with each parameter having a clear description and examples. The description itself adds no parameter details, so it meets the baseline 3 when schema does the heavy lifting.

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 (check) and resource (alignment with recorded decisions), and distinguishes itself from siblings like dependency_check and decision_memory by naming what it validates. It doesn't explicitly differentiate from decision_memory, which likely stores decisions, but the purpose is clear.

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 tells the agent when to call: 'BEFORE suggesting a major tech change, new library, or architecture shift.' This is a clear pre-action trigger that no sibling provides.

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?

Annotations already declare readOnlyHint=false, destructiveHint=false and idempotentHint=false, so the mutation/idempotency profile is covered structurally. The description adds only the notion of 'supersede' (implying the prior decision is retained rather than deleted), but says nothing about persistence scope, permissions, or what happens to state on update/supersede beyond that inference.

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 redundancy: the first front-loads the action set and resource, the second front-loads the trigger condition. 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 20-parameter, five-action tool this is thin. The description lists only four actions and omits check_alignment entirely, which is exactly where it collides with the sibling check_decision_alignment tool, and it gives no indication of what list/record returns (no output schema exists to compensate).

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 every one of the 20 parameters carries its own inline '(for <action>)' hint, so the schema does the heavy lifting. The description adds no per-parameter meaning beyond what the enum documentation already supplies, so the baseline 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 names specific verbs (record, list, update, supersede) tied to a concrete resource (the developer's architectural and tech decisions), so the tool's function is unambiguous. It does not explicitly differentiate itself from the overlapping siblings check_decision_alignment or agent_memory, which keeps it out of 5 territory.

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?

A clear triggering condition is given: 'Call when the user makes, changes, or asks about a settled decision or convention.' That covers the main invocation contexts, but there is no when-not guidance and no routing advice against the sibling check_decision_alignment tool even though this tool also exposes a check_alignment action.

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?

Annotations already declare readOnlyHint and idempotentHint, so safety is covered. The description adds genuinely new behavioral context: the tool returns either a single verdict (exact version) or a set of safe releases (constraint), which is important since there is no output schema. It does not clarify what "safe" means (security vs. compatibility vs. licensing) despite sibling vulnerability_scan implying overlap.

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 filler. The core purpose is front-loaded as a question, and the call-before-writing instruction is tight and 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?

With no output schema, the description correctly supplies the two return modes (verdict vs. safe releases in a constraint), which is the key missing structured information. The residual gap is the undefined meaning of "safe" and no failure/unknown-package behavior, but for a read-only advisory tool this is close to 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 one parameter and its nested fields (ecosystem, package, to, from) are fully documented in the schema. The description's constraint examples ("7.x", "~=3.1") and ecosystem list repeat the schema rather than extending it, so the baseline 3 applies.

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

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

Opens with a concrete question that names the resource and the decision it supports ("Is a dependency version safe to write?"), and scopes it to an exact version or a constraint across npm/crates.io/PyPI/Go. The verb+resource are unambiguous, but it never distinguishes itself from close siblings like vulnerability_scan or dependency_health, so the agent cannot tell from the description alone which of the safety-oriented tools applies.

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?

Gives an explicit trigger and timing: "Call BEFORE writing any version to a manifest: add, pin, upgrade, bump, downgrade." That is strong condition-setting, but it offers no when-not guidance and never names an alternative tool, so the sibling routing is left to inference.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety and network-access profile is covered. The description adds that results span four ecosystems and include CVE/deprecation counts, but says nothing about pagination, cost, or freshness of the data source.

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, both earning their place: the first states scope and data covered, the second states the invocation trigger. Front-loaded and free of 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?

With no output schema, the description carries the burden of signalling the return content, which it does by naming freshness, deprecation and CVE counts. The only gap is return shape/pagination, minor for a read-only listing 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% and all four parameters (limit, sort_by, include_dev, ecosystem_filter) are documented with defaults and enum meanings in the schema itself. The description adds no parameter-level detail, so the baseline 3 applies.

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

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

The description names a concrete verb-less but specific resource: version freshness, deprecation and CVE counts across npm/Rust/Python/Go. An agent can tell it produces a dependency-health report. However, it does not distinguish itself from close siblings such as vulnerability_scan or dependency_check, leaving overlap ambiguous.

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

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

It gives a clear trigger: 'Call when the user asks whether their dependencies are outdated, stale or need updating.' This is explicit when-to-use guidance. It stops short of naming alternatives or when-not-to-use, so the agent must infer that vulnerability_scan handles deeper security work.

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?

Annotations already declare readOnlyHint and openWorldHint, so the agent knows this is a safe, externally-sourced read. The description adds the meaningful constraint that results are limited to named dependencies the project uses, which is real behavioral context. It says nothing about recency window, ranking, or how the ecosystem is resolved, so a 3 is appropriate with annotations carrying the safety profile.

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, and the scoping constraint is front-loaded before the usage trigger. 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 two-param, no-required-argument read tool with annotations covering safety and no output schema, the description is essentially complete. The only unaddressed item is how 'the project's ecosystem' is determined, which is minor.

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%: limit and min_points are both documented with defaults in the schema. The description adds no parameter detail beyond that, so the baseline 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 gives a specific verb+resource: it surfaces recent Hacker News discussions, filtered to dependencies or frameworks the project actually uses. That scoping constraint ('actually uses') is the distinguishing feature and is stated plainly. It stops short of naming which sibling to prefer for adjacent questions (e.g. what_should_i_know), so it is clear but not fully sibling-differentiated.

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

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

It gives an explicit trigger: 'Call when the user asks what is new or being discussed in their ecosystem.' That is a clear use context. There is no when-not guidance or named alternative for overlapping questions like general project news, which keeps it below a 5.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are covered. The description adds the useful detail of what the payload contains (role, stack, interests, exclusions, project context), which matters because there is no output schema, but it says nothing about freshness, caching, or empty-result 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?

Two sentences, no waste. The content listing comes first and the invocation guidance second, which is the right front-loading for a tool meant to be called early.

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 read-only tool with two optional boolean flags, the description covers purpose, contents, and invocation timing, and the absence of an output schema is offset by the enumeration of returned context categories. Minor gaps remain around what happens when context is missing for a new user.

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 both parameters (include_ace, include_learned) are documented with defaults in the schema. The description never mentions either toggle, so it adds no meaning beyond the structured fields; baseline 3 applies.

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

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

The description names a specific resource (the user context that 4DA holds) and enumerates its contents: role, tech stack, interests, exclusions, detected project context. It is clear what the tool returns, but it does not distinguish itself from siblings such as what_should_i_know or agent_memory, which also surface user-relevant knowledge.

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

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

It gives an explicit trigger and priority: 'Call FIRST when you need to know what the user works on before answering or recommending.' That tells the agent both when to reach for it and that it should precede other calls. It stops short of naming an alternative or a when-not-to-use condition.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety and external-registry profile is covered. The description adds the multi-source nature of the result (changelog plus project-local import scan), which is useful. It does not, however, disclose cost, latency, or rate-limit behavior despite hitting a registry and indexing the codebase.

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 scope and the exact output contents, then the call trigger. No filler and nothing redundant with the schema.

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 read-only, open-world tool with a fully described five-parameter schema and no output schema, this covers what the tool returns and when to invoke it. A small gap remains around cost/latency and how the from_version/to_version defaults interact when the lockfile is absent.

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%: every parameter including the package-name format conventions, the ecosystem enum, the version defaults, and the concise/detailed response format is documented in the schema. The description adds no semantics beyond that, so the baseline 3 applies.

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

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

States a specific verb (report what changes) on a specific resource (one dependency between installed and target version) and enumerates the exact payload: changelog per release, breaking changes, deprecations, security fixes, and the project's own importing files. That enumeration distinguishes it from siblings like dependency_check and upgrade_planner.

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?

Gives an explicit trigger: 'Call before upgrading or bumping a dependency.' That is clear context, but it names no alternative, so an agent cannot tell from this text whether upgrade_planner or vulnerability_scan is the better fit for a given situation.

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?

Annotations cover the safety profile (readOnlyHint=true, openWorldHint=true), so the bar is lower. The description adds meaningful behavior beyond them: it discloses two operating modes — the app-level 'work order' with per-line targets and manifest-vs-lockfile fixes when available, falling back to the smallest fixing version otherwise. It omits any note on cost, latency, or scope limits.

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?

Purpose, parameter anchor, and trigger are front-loaded in two compact sentences with little waste. The dense parenthetical ('per-line targets, manifest vs lockfile fix') is efficient though heavily jargon-laden for a reader without '4DA' 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?

With no output schema, the description carries the burden of explaining returns; it sketches the shape (per-line targets, minimal fixing versions) but through unexplained jargon, and never clarifies how this plan relates to upgrade_impact or vulnerability_scan. For a five-parameter planning tool it is adequate but leaves real gaps.

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

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

Schema description coverage is 100% with five parameters, so the baseline is 3. The description reinforces project_path's singular scope and the app-vs-standalone plan mode, but that mode distinction is already documented in the project_path schema text, so it largely repeats rather than extends the structured data.

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 opening clause states a specific verb+resource ('Prioritized upgrade plan for one project'), which is clear enough to separate it from siblings like upgrade_impact or vulnerability_scan. However, the elaboration ('the 4DA app's work order') leans on unexplained internal jargon rather than describing the tool's distinct role relative to those 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?

'Call when the user asks what to upgrade' is an explicit, actionable trigger that tells the agent exactly when to reach for this tool. It stops short of naming when-not conditions or pointing to upgrade_impact/vulnerability_scan as alternatives, so it is clear context without 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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and network egress are covered. The description adds real context beyond them: it scans lockfiles rather than source, includes transitives, reports fix versions and pin locations, and queries OSV.dev for advisory data. It stops short of describing report size/limits, which is left to 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?

Front-loads the scan scope and ecosystems, then the trigger and the alternative in two short sentences. The opening clause is semicolon-dense but every clause (ecosystems, transitives, fix versions, pin locations) earns its place; nothing is padding.

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

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

With no output schema, the description usefully summarizes what the report contains (fix versions, where each is pinned) and that transitives are included, complementing a fully documented 7-parameter schema. It omits mention of caching/refresh and report truncation behavior, but those are covered by the schema's own parameter docs.

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 carries the semantics of all seven parameters. The description only echoes the `package` scoping behavior and alludes to fix/pin output; it adds no syntax, format, or default information the schema does not already provide. Baseline 3 applies.

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

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

Names a specific verb (scan), resource (this project's lockfiles), the ecosystems covered (npm/pnpm/yarn/bun, Cargo, Python, Go), and the data source (OSV.dev). It also carves out the single-package variant (`package`) and names the sibling it is not (dependency_check), so an agent can separate it from alternatives without opening a schema.

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

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

Gives an explicit trigger ("Call when asked about security or CVEs") and an explicit routing rule to an alternative with its condition ("To vet a version first: dependency_check"). It also directs single-dependency questions to the `package` parameter rather than a full report.

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?

Annotations cover the safety profile (readOnlyHint=true, openWorldHint=true), and the description adds what the agent actually receives — a bundled brief with installed versions, confirmed vulnerabilities, releases since, prior decisions, and a delegation verdict. Since there is no output schema, this enumeration of return contents is valuable behavioral disclosure beyond the annotations.

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 output contents are front-loaded in the first sentence and the usage call-to-action follows immediately. It is dense but every clause maps to a real behavior; only the long comma list slightly pressures 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?

For a read-only aggregator with no output schema, the description supplies what the agent needs: the bundled content, the ideal invocation timing, and the fact that lockfiles/project context determine scope. Nothing critical 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 all three parameters are already documented in the schema. The description adds only a light hint about the task content ('the dependencies and package families it names'), which is essentially restating what the schema already says. Baseline 3 applies.

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

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

The description names a concrete deliverable (a pre-task briefing) and enumerates its contents — dependencies, installed versions, vulnerabilities, releases since, decisions, a delegation verdict. This clearly separates it from single-purpose siblings like vulnerability_scan or dependency_health, though it never names a sibling explicitly.

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

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

It gives a clear trigger: 'Call BEFORE a non-trivial task, especially one that changes dependencies.' That is actionable timing guidance. However, with 11 siblings there is no when-not guidance and no named alternatives (e.g., call vulnerability_scan instead when you only need CVEs).

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