AgentBreakWatch

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), but the description adds useful context: no authentication is required, the registry scope is 258 live entries, and the tool returns a structured JSON report with actionable pin commands. It does not describe failure modes or how large manifests are handled, but it adds real behavioral value 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 description is three sentences with no filler, front-loading the read-only audit purpose before listing what it detects and the authentication/return characteristics. Every sentence contributes: purpose, detection scope, and operational traits.

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 single-parameter, read-only audit with no output schema, the description gives enough context to call it correctly and understand the general shape of the response (structured JSON with flags and pin commands). It could specify the report fields or how no-drift results are represented, but the essential context 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?

There is a single required parameter with 100% schema description coverage, so the schema already explains that manifest accepts raw .mcp.json, package.json, requirements.txt, or a newline-separated package list. The description echoes the accepted formats but adds no syntax, validation, or formatting guidance beyond the schema. 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 names a specific verb and resource: a read-only audit of a manifest string against a live registry of AI Agent SDKs and MCP servers. It also states what the audit detects (major version drift, unpinned @latest servers, outdated dependencies), which makes the tool's role distinct from the sibling list/get tools. It stops short of explicitly naming those siblings as 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?

Usage is implied by the phrase 'audit of a package.json, requirements.txt, or .mcp.json configuration string,' so an agent can infer this is the tool for checking a whole manifest. However, there is no explicit when-to-use or when-not-to-use guidance relative to get_package_stability, list_volatile_packages, or get_archived_mcp_replacements.

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, idempotentHint=true, destructiveHint=false, and openWorldHint=false, covering the safety profile. The description adds useful context: 'Takes no parameters and requires no authentication.' However, it does not describe the return format or any other behavioral traits beyond what annotations provide. A 3 is appropriate given the lower bar with 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?

Two tightly written sentences with the core purpose front-loaded. Every sentence earns its place: the first defines the lookup and its scope, the second clarifies no parameters and no authentication. No waste or redundancy.

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 lookup with rich annotations and no output schema, the description is nearly complete. It states that the return is a 'complete migration matrix' but does not detail its structure or contents, which is a minor gap. The no-auth and no-params statements round out the call context well.

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 baseline is 4. The description explicitly confirms 'Takes no parameters', which aligns with the empty schema and reinforces that no input is needed. No further parameter semantics are required.

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 ('lookup') and a well-defined resource ('migration matrix for archived or frozen @modelcontextprotocol/server-* reference packages and their official 2026 vendor-maintained replacements'). It does not explicitly name or differentiate from siblings like check_stack_drift, but the domain is distinct enough that an agent can infer the difference. Score 4 because sibling differentiation is absent.

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 states what the tool does but gives no guidance on when to use it versus alternatives such as check_stack_drift or get_package_stability. It also provides no exclusions or preconditions beyond 'requires no authentication'. An agent must infer the use case from the purpose statement alone.

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, idempotentHint, and destructiveHint=false, so 'Read-only lookup' is largely redundant. The description earns credit for what annotations cannot convey: it enumerates the returned signals (publish timestamp, 90-day velocity, 0-100 stability score, tools/list drift risk, before/after migration code), which is meaningful given there is no 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?

Two sentences, zero filler: the capability and returned signals come first, the disambiguation against the sibling last. The output enumeration is dense but each item carries information an agent needs absent an output 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 single-parameter, read-only, non-destructive lookup with no output schema, the description supplies the return-value surface, the input scoping rule, and the sibling routing. Nothing material is missing 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 100% and already supplies examples, so the baseline is 3. The description still adds semantic framing — the package must resolve to 'a single AI Agent SDK or MCP server' and may be a name or a slug — clarifying that scoped/glob or multi-package inputs are not intended.

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?

Specific verb ('Read-only lookup') plus a precisely scoped resource ('live npm or PyPI version... for a single AI Agent SDK or MCP server'), and it enumerates exactly what the lookup returns. An agent can distinguish this from check_stack_drift 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?

Explicitly routes the agent: 'Prefer this over check_stack_drift when inspecting one specific package by name or slug,' which implies the sibling for multi-package/stack-level checks. It does not address the other siblings (list_volatile_packages, get_archived_mcp_replacements), so the coverage of alternatives is partial rather than complete.

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 establish the read-only, idempotent, non-destructive, closed-world safety profile. The description adds useful behavioral context beyond annotations by identifying the live telemetry source and specifying descending sort order by 90-day release velocity.

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 wasted language. The core purpose and ranking are front-loaded, and the filter summary follows efficiently.

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 list tool with three optional parameters and no output schema, the description is mostly complete: it covers purpose, source, sorting, and filters. The remaining gap is that it does not describe the shape of returned package records, which is more relevant because no output schema exists.

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 input schema already documents kind, limit, and category in detail. The description echoes the filters and the 1-50 limit range but does not add syntax or usage nuance beyond what the schema provides, making the baseline 3 appropriate.

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

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

The description gives a specific verb and resource: it lists fastest-changing or highest schema-drift-risk AI Agent SDKs and MCP servers. It clearly defines the ranking basis as descending 90-day release velocity, but it does not explicitly distinguish itself from siblings such as get_package_stability.

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 indicates the tool is a read-only query and summarizes its filter options, implying it should be used to retrieve volatile package rankings. However, it never states when to use this tool instead of siblings like get_package_stability or check_stack_drift, nor does it provide explicit exclusions.

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