FDE Lessons API

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

With no annotations, the description carries the full burden and does well: it discloses that the tool is free, that it lists metadata only, and that the paid body is withheld. This gives the agent an accurate expectation of what the tool returns and its limitation.

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

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

Two short sentences, front-loaded with the key selling point ('FREE') and the core action ('List every...'). Every phrase earns its place, with 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?

For a zero-parameter, no-output-schema tool, the description is complete: it states scope, fields returned, cost, and the recommended sequencing. The agent knows exactly what the tool does and when to call 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 tool has zero parameters, so the baseline is 4. The description adds meaningful context about the output even though no parameter semantics are needed.

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 ('List') and a clear resource (every Forward Deployed Engineering rule, playbook, and checklist phase) along with the exact fields returned (id, title, phase, tags). This is unambiguous and distinguishes the tool as a catalogue/meta-listing rather than a content-specific sibling.

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 tells the agent to call this tool first 'to see what is on offer before paying for anything,' which is clear when-to-use guidance. It doesn't explicitly name sibling alternatives, but for a zero-parameter catalogue tool this is sufficient.

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 burden. It clearly discloses the mandatory payment ('Requires a machine payment (MPP over Stripe)') and the unpaid fallback ('returns the exact payment challenge and the URL to retry against'). It does not describe the full return format, but it covers the most important behavioral quirks.

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 short and front-loads the essential 'PAID' fact before the purpose. The standalone 'PAID.' is slightly redundant with 'Requires a machine payment...', but every other sentence contributes necessary information about behavior and failure mode.

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-optional-parameter tool with no annotations and no output schema, the description supplies the key behavioral context: paid operation, full or topic-filtered result, and unpaid response. It lacks explicit sibling routing, but that is already penalized under usage guidelines rather than completeness.

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 the topic parameter is already described as 'Optional keyword filter.' The description's 'subset matching a topic' essentially restates the schema without adding formatting, syntax, or matching details, 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?

States a specific verb and resource: 'Return the full Forward Deployed Engineering ruleset, or the subset matching a topic.' The 'full' and 'PAID' markers distinguish it from the sibling fde_lessons_preview, but no sibling is explicitly named.

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: use when you need the paid/full ruleset, optionally narrowed by topic. The payment prerequisite is clear, but the description does not explicitly say when to use fde_lessons_preview or other siblings, nor does it state exclusions or alternatives.

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 burden. It clearly signals a non-mutating 'Return' operation and adds useful detail about the returned content: each rule includes the real incident and an implementable agent-behavior constraint. It does not discuss auth or rate limits, but for a benign read-only preview this is a minor 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 short and front-loaded with 'FREE', and the content-structure detail earns its place. The only slight flaw is the redundancy between 'FREE' and 'no payment required', but overall it remains compact and scannable.

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 one optional parameter and no output schema, the description gives enough about what is returned and the free-access condition for an agent to call it correctly. The main gap is not explaining how it relates to fde_lessons_full, but the low complexity makes this non-blocking.

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, 'topic', is fully described in the input schema with examples ('verify', 'cache', 'deploy'), and schema description coverage is 100%. 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 action and resource: 'Return the foundational Forward Deployed Engineering rules in full' and explains what each rule contains. It is clear, though it does not explicitly contrast this tool with sibling fde_lessons_full beyond the 'FREE' and 'foundational' framing.

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 free/no-payment phrasing and 'foundational' scope imply this is the no-cost entry-point lessons tool, but the description never explicitly says when to use it over fde_lessons_full, fde_catalogue, or fde_playbook. No exclusions or alternative conditions are given, so routing must be inferred.

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 present, so the description carries the full burden. It discloses that the tool is 'PAID' and that it returns runbooks with ordered, checkable steps. However, it does not mention side effects, authentication, or error behavior. For a simple read-like tool, this is adequate but not comprehensive.

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 short sentences that front-load key information: cost, what it returns, scope, and usage timing. No unnecessary words; 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 one optional parameter and no output schema, the description provides the essential information: what it returns, when to use it, and examples. It lacks details on edge cases (e.g., empty result) but is sufficient for a simple retrieval 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 'topic' is documented with an example. The tool description reinforces the example topics (DNS migration, static-site change) but adds no new semantics beyond the schema. 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 clearly states the tool returns situational runbooks with ordered, checkable steps, and specifies the domain (DNS migration and static-site change). It does not explicitly name sibling tools for differentiation, but 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?

It gives explicit timing guidance: 'Use before executing that class of operation, not after it fails.' This clarifies when to use it (before) and when not to (after failure). It does not name alternatives, but the usage context is clear.

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 burden. It discloses that the operation is paid ('PAID.'), indicates it is a read-style return, and notes the intended deploy-time use. It does not describe response behavior or rate limits, but for a checklist retriever the key traits are 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?

Three short segments ('PAID.', purpose, usage intent) are tightly packed with no filler, and the key warnings are front-loaded. Every sentence contributes information an agent needs.

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, no output schema), the description covers purpose, usage timing, paid status, and output content. It could name sibling alternatives for routing, but nothing necessary 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 optional 'phase' parameter is already fully documented with its allowed values. The tool description adds no additional parameter semantics, which is acceptable per 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 uses a specific verb ('Return') and identifies a distinct resource (the pre-ship checklist) with clear content ('every gate ... each with the concrete failure it prevents'). It is distinct from sibling tools by resource name, though it does not explicitly contrast itself with fde_playbook or fde_catalogue.

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 'Designed to be called before every deploy' gives explicit timing/context for using this tool. It does not mention exclusions or alternatives, so it stops short of full when/when-not 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?

There are no annotations, so the description carries the behavioral burden. It discloses that the tool is paid, returns only corrections rather than the full dataset, and is backed by a monthly re-read against vendor pages. It doesn't mention pagination or exact return shape, but the core behavioral context is well covered.

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 focused sentences with no filler. The paid status and core action are front-loaded, followed by useful context about freshness and cost comparison.

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 read tool with no output schema, the description covers purpose, filtering behavior, data freshness, cost, and how it compares to alternatives. It doesn't specify the exact return format, but that is a minor gap given the tool's simplicity.

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 fully describes the only parameter ('Optional YYYY-MM-DD. Defaults to 30 days back'), so the description adds little semantic value for the parameter. With 100% schema description coverage, 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 uses a specific verb ('Return') and a specific resource ('dated Agent Pricing Index corrections'), and immediately distinguishes itself from the full-dataset tools by saying 'what changed, not the full 47-row dataset.' There is no ambiguity about the tool's purpose.

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 selection context—'when you only need to know what moved'—and contrasts itself with 'fde equivalent full-dataset calls' as cheaper. It doesn't name a specific sibling tool or state explicit when-not-to-use conditions, but the guidance is enough for an agent to choose correctly.

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