The2410 Projects

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

Discloses return content (fit, services, indicative pricing, project_context_id, next_actions), routes small tasks to route=small_task, and explicitly bounds itself against being a detailed plan or contractual estimate. Annotations confirm read-only, consistent with an evaluation 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?

Front-loaded purpose, then trigger, then outputs and boundaries. Four sentences, each earning its place, though the boundary sentence could be trimmed slightly.

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?

No output schema, and the description covers key returned fields and the small-task branch. A bit more on the structure of 'fit' or next_actions would help, but the essential call-shaping info 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?

Schema coverage is 100%, so parameter meanings are already fully documented, including the omit-for-new-project rule. Description adds no syntax or format detail beyond the schema baseline.

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

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

States a specific verb (evaluates/assesses fit) and resource (custom software project described by a customer) clearly. Distinguishes itself from siblings like plan-project-tool and submit-project-inquiry-tool by scope.

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 clear trigger ('Use it when a customer describes a new project or request') and an implicit branch for small tasks. Does not name explicit alternatives (e.g., when to use plan-project-tool instead), but the trigger is 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?

Annotations already declare destructiveHint=true, readOnlyHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful context beyond them: the call sends an email to the team, the confirmation is sent separately by the team, the consultation is in English, and it warns against duplicate submissions.

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?

Sentences are front-loaded with purpose first, then prerequisites, then inputs and post-conditions. Each sentence carries usable information, though the language note and confirmation note could be tightened slightly.

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 output schema, the description covers the trigger conditions, required inputs, the out-of-band confirmation email, and idempotency. It does not mention failure modes such as an already-taken slot, which would round it out.

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 explains all five parameters, and the baseline is 3. The description only restates that name and email should be provided, adding no syntax or format detail beyond the schema; slot_id and project_context_id are left to 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 gives a specific verb and resource ('Register a consultation... by sending an email') and ties it to the workflow of a named sibling (get_consultation_slots). It does not contrast itself with other submission siblings like submit-project-inquiry-tool, so it stops short of full 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?

It states exactly when to call it (after the user selects a slot from the latest get_consultation_slots response and confirms), what to supply, and an explicit do-not condition ('Do not submit the same booking again after a successful response'). This is precise 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?

Annotations already establish readOnly/non-destructive/closed-world, and the description adds genuinely new context: the computation inputs (project context, estimated business days, preferred start) and the caveat that returned dates are indicative, not contractual. It stops short of describing the response shape (e.g. start vs. end date fields).

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 with the purpose front-loaded and the usage trigger immediately after. The final disclaimer sentence earns its place, though the opening two clauses overlap slightly on "delivery window".

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

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

For a 2-parameter read-only tool with an output schema absent, the description supplies the key missing piece by characterizing the return value as indicative dates and flagging the non-contractual nature. It does not enumerate which date fields come back, a small remaining gap.

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

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

Schema description coverage is 100%, so both parameters are already fully documented in the schema, including the ASAP/null fallback for preferred_start. The description adds only a restatement that preferred start feeds the calculation, which is the expected baseline-3 level of added 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?

States a specific verb and resource ("Check The2410's indicative delivery availability") and narrows scope to the customer's software project. No sibling tool touches delivery timing, so the agent can route here 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?

Explicitly names the triggering intent: "Use this tool when the user wants to know when The2410 could start the project and the approximate delivery window." It gives clear positive guidance but names no exclusions or alternatives among siblings.

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 read-only, non-destructive, closed-world, and the description usefully adds behavioral facts beyond them: it consumes existing project context and changes nothing ('does not change the project context, plan, or estimate'). Return behavior (up to five, relevance-ordered) is also disclosed. Not exhaustive on result format, so a 4 rather than 5.

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 tight sentences: purpose first, usage condition second, side-effects last. Every sentence carries distinct information with no 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?

For a simple single-param read tool with no output schema, the description covers purpose, trigger, input source, result count/ordering, and non-mutating behavior. Nothing needed to invoke it correctly 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 coverage is 100% and there is a single parameter, so the schema already explains project_context_id fully. The description mentions the tool 'uses the existing project context' but adds no syntax or format detail beyond the schema's UUID note.

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 ('Find published The2410 case studies') scoped to the customer's software project. It is distinguishable from planning/inquiry siblings, which do not retrieve reference material.

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 a clear trigger condition: 'Use this tool when the user wants examples of similar work or relevant project experience.' It does not name an alternative tool or a when-not-to-use case, so it falls short of 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 cover the safety profile (readOnly, non-destructive, closed-world), so the description's added value is the return contract: up to ten slots, earliest-to-latest ordering, and requested timezone. It also clarifies the non-mutating boundary, but omits whether an empty result is possible.

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 tight sentences: purpose first, then trigger, then the return contract and the non-booking caveat. No filler, and the most decision-relevant routing 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?

With no output schema, the description steps in to describe the return shape (count and ordering) and timezone handling, which is the critical missing piece. It does not say what a slot object actually contains (e.g., start/end times or identifiers), leaving a small gap for a discovery 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%, so date_to/date_from/timezone semantics, defaults, and the 31-day span cap are already documented. The description only restates timezone handling and adds no format or constraint detail 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?

States a specific verb and resource ('Get available consultation times with The2410') scoped to the current software project, and explicitly separates itself from the booking flow. An agent can distinguish it from the sibling book_consultation without opening either schema.

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

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

Gives an explicit trigger ('when the user wants to speak with The2410 or choose a consultation time') and an explicit exclusion ('does not reserve a slot or create a booking'), which implicitly routes booking intent elsewhere. It stops short of naming book_consultation as the alternative for reservation.

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 annotations already declaring a non-read-only, destructive tool, the description still adds real context: PII is collected and stored, the customer may be contacted, expansion runs a detailed analysis server-side, and the output is a preliminary estimate rather than a contractual offer. The one gap is the destructiveHint itself — it never says that re-calling replaces or wipes the previously saved plan, which is exactly the risk an agent needs to know about.

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 is front-loaded in the first sentence and each subsequent sentence carries a distinct fact (input choice, status semantics, estimate caveat, consent, update behavior). Slightly repetitive in mentioning the required name/email twice, but no sentence 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 7-parameter mutating tool with no output schema, the description covers inputs, consent/privacy, the meaning of module statuses, and update behavior. It stops short of describing the returned plan's shape (price range format, module list) and the replace-on-rerun consequence, which are the remaining gaps.

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

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

Schema coverage is 100%, so the schema already documents every parameter including the 'omit to keep saved value' semantics. The description usefully clarifies the either/or relationship between project_context_id and project_description and that name/email are required for the backend analysis, but otherwise restates schema content, 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 first sentence states a specific verb and resource set (create a preliminary project plan, price range, effort estimate), and the second scopes the intent to understanding functional modules and open requirements. It is clearly distinguishable from book_consultation or send-feedback-tool, but it never names the closest-seeming siblings (analyze-request-tool, prepare-project-inquiry-tool) to draw the boundary 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 concrete invocation conditions: provide an existing project_context_id or a project_description for a new project, and it states that re-calling the tool updates the plan. What's missing is any exclusion — nothing says when to prefer analyze-request-tool or prepare-project-inquiry-tool instead, so the agent must guess among overlapping planning/preparation siblings.

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 destructiveHint=true, and the description clarifies that the only mutation is the draft itself and that nothing is submitted, emailed or deleted, which materially reduces mis-invocation risk. It also discloses the return contents and the caveat that delivery dates may be indicative. A minor gap remains: it never says whether re-calling overwrites prior draft state versus merging.

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-loaded with the verb and resource, then prerequisites, then behavior and exclusions in a logical order. Every sentence carries information, though the returned-field enumeration is slightly list-like and could be tightened.

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 compensates by describing the returned fields (fit, offering, estimate, modules with price and effort) and the delivery-date caveat. Prerequisite, mutation semantics, and non-goals are all covered for a tool with a nested 3-parameter schema.

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 nested contact object, its required name/email and optional company/phone are already fully documented in the schema. The description restates the required/optional split without adding format or validation semantics, so it sits at 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 ('Prepare a project inquiry draft') plus the scope ('for the customer to review before it is submitted'). It also explicitly separates itself from the write path ('This tool does not submit the inquiry'), which distinguishes it from the sibling submit-project-inquiry-tool.

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 prerequisite ('Run plan-project-tool first and provide the existing project_context_id') and an explicit re-use rule ('The draft can be changed by calling this tool again'). Combined with the negative statement about submitting, an agent knows both when to call it and when not to.

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 show readOnlyHint=false, destructiveHint=false, openWorldHint=false, but the description adds crucial behavioral context beyond that: it advises showing the message to the customer before sending and waiting for confirmation, and explicitly warns against including sensitive data. This goes beyond the structured hints, though it could say more about what happens after sending or error handling.

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, well-structured paragraph with no filler. It front-loads what the tool does, then gives usage conditions, confirmation instructions, parameter guidance, and a security warning in logical order.

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 6-parameter tool with no output schema, the description covers purpose, usage trigger, confirmation workflow, parameter semantics, and sensitive-data restrictions. Nothing essential is missing for an agent to call it correctly.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining that name and email are optional and should be included only if the customer wants a reply, and that project_context_id/order_id should be added only for specific project/order feedback, clarifying their conditional use beyond the schema's bare description.

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 (send), resource (feedback), recipient (The2410 team), and enumerates the content categories, which clearly distinguishes it from the sibling order/service 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?

It explicitly states 'Use only when the customer wants to share feedback' and gives a clear workflow: show the message to the customer and send only after they confirm. This is a strong usage boundary with an implicit alternative (don't use otherwise).

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 flag a non-read-only, destructive write, but the description adds genuinely non-obvious behavior: the inquiry is emailed to The2410, no automatic confirmation goes to the customer, and it reuses saved analysis and plan state. It stops short of explaining what 'destructive' means here (e.g., whether the context is consumed or comments overwritten), so it is not fully complete.

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 and precondition are front-loaded and the sentences are short. There is mild redundancy ('emails the inquiry to The2410' is stated twice, and the required/optional field listing duplicates the schema), but nothing is padded or off-topic.

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 write tool with no output schema, three parameters, and a nested object, the description covers the key operational facts an agent needs: precondition, side effect, absence of customer confirmation, and idempotency guidance. Failure behavior and what a successful response returns are not addressed, which 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?

Schema description coverage is 100% and the nested contact object is fully documented, so the schema carries the parameter burden. The description mostly restates required/optional fields ('Name and email are required; company and phone are optional') and the provenance of project_context_id already noted in the schema, adding little new meaning.

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 ('Submit the customer's project inquiry') and adds the delivery channel ('to The2410 by email'). Its workflow positioning ('after the customer has reviewed the inquiry') lets an agent separate it from the adjacent prepare-project-inquiry-tool and the analyze/plan tools 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?

It states a precise precondition for use ('after the customer has reviewed the inquiry and explicitly asked to submit it') and an explicit when-not-to-use rule ('Do not repeat this call after a successful submission'). The usage boundary is unambiguous, even though it does not name the sibling tool by name.

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