Trickl

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

Annotations only supply readOnlyHint=false; the description carries the rest and does so richly: it discloses that chunk and deposit reversals happen in the ledger only (not real funds), that a refundable deposit is involved, and that a goal.cancelled event is emitted. That is exactly the side-effect disclosure an agent needs before mutating state.

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

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

One sentence, front-loaded with the action, the resource, and the endpoint before the parenthetical side-effect detail. No filler 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 single-parameter mutation with no output schema, the definition covers action, route, and consequences well. It stops short of describing the response body or failure modes (e.g., cancelling an already-cancelled goal), which would close the 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?

There is a single parameter with 100% schema description coverage, and the schema already states the goalId comes from create_test_goal. The description only echoes :goalId as a path segment, adding no new semantics, 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?

Names a specific verb (cancels) and resource (sandbox goal), plus the exact HTTP route POST /goals/:goalId/cancel. It is immediately distinguishable from siblings like create_test_goal, get_goal, and simulate_goal_event.

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 'as the user's server would when a customer cancels' tells the agent this is a simulation of a real cancellation flow, which is clear context for choosing it. It doesn't explicitly name when to use simulate_goal_event versus this tool, or state prerequisites such as the goal needing to exist in an uncancelled state.

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?

readOnlyHint=true already declares the safety profile, and the description adds value beyond that: it names the fields surfaced on success and states that failures carry a user-actionable remediation message. It doesn't discuss rate limits or auth requirements, but those are largely irrelevant for a no-arg key check.

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: purpose first, execution ordering and failure handling second. No filler and no repetition of the title or annotations.

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 parameters and no output schema, the description supplies the missing return-value information itself (platform, scopes, mode) plus error behavior. An agent has everything needed to decide to call it first and how to interpret both outcomes.

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 takes zero parameters, so the schema carries nothing the description needs to compensate for; baseline 4 applies. The description correctly adds implicit context that the call operates on ambient connector configuration rather than inputs.

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 ('Confirms this connector's test key works') and scopes it to the sandbox/test context, which separates it from all listed siblings that operate on goals, docs, or webhooks. It also previews the returned fields (platform, scopes, mode), so an agent knows exactly what the call answers.

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?

'Run it before the other sandbox tools' gives an explicit ordering constraint, and the failure clause explains what to do when it doesn't pass. No exclusions are stated, but for a zero-parameter validation call there is no meaningful alternative to disambiguate against.

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 only supply readOnlyHint=false, so the description carries most of the burden: it declares no money moves, names the endpoint, and specifies the three return values (goalId, paymentUrl, clientSecret), including the hosted-vs-embedded distinction. It does not state auth/rate-limit behavior or webhook side effects, but the value-add over annotations is substantial.

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 with zero filler; the operation, the safety guarantee, and the return shape are front-loaded in that 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?

With 11 params, nested metadata, and no output schema, the description usefully explains return values and the no-charge guarantee. Minor gaps remain around error behavior and what happens with callbackUrl/cancelUrl redirects, but nothing essential 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 coverage is 73%, so the schema already documents most parameters in detail (deadline window, depositAmount rules, frequency semantics). The description adds only a global unit/currency clarification ('integer cents, USD'), which largely restates targetAmount's own schema description. 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?

States a specific verb and resource ('Creates a goal') plus the underlying endpoint and mode ('test key'), and immediately rules out side effects ('No money moves'). This cleanly separates it from cancel_test_goal and the other test-mode siblings without ambiguity.

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 test-key framing implies this is the sandbox path, but the description never states when to choose it over a live counterpart or what must happen first. The prerequisite (register_test_provider) only surfaces in the schema's providerLinkCode description, so guidance here is implied rather than stated.

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

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

With readOnlyHint=true already declaring safety, the description adds useful context by specifying the GET endpoint and the exact fields returned (status, amounts saved, buyer, deadline). It does not cover auth, error behavior, or rate limits, but for a simple read operation this is solid additional disclosure.

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

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

The description is a single front-loaded sentence with no wasted words. It states the operation, endpoint, and returned fields 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 simple read tool with one required parameter, readOnly annotations, and no output schema, the description gives enough context to call it correctly. It names the returned data fields, though it could add minor operational details such as not-found behavior.

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 the sole parameter and that goalId comes from create_test_goal. The description adds little beyond showing :goalId in the endpoint path, which is baseline for high schema coverage.

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

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

The description uses a specific verb ('Returns') and resource ('sandbox goal's current state'), making the operation clear. It does not explicitly distinguish itself from siblings like create_test_goal, cancel_test_goal, or simulate_goal_event, but the retrieval 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?

There is no explicit guidance on when to use this tool versus alternatives. The description implies retrieval of current state, and the schema mentions goalId comes from create_test_goal, but it never states conditions, exclusions, or named 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?

Annotations already establish that this is a read-only operation, and the description adds meaningful behavioral context: it explains that the tool either presents integration options or returns a step-by-step plan containing keys, API calls, webhook handling, storage guidance, and sandbox verification. It does not discuss error behavior or output formatting, but those are minor gaps given the read-only annotation.

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 "Start here," then efficiently covers both operating modes and the contents of the returned plan. Every sentence adds useful information without 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 read-only, one-optional-parameter onboarding tool with no output schema, the description provides enough detail to call it correctly: it explains what happens with and without the parameter and what the resulting plan covers. Nothing critical is missing for an agent to decide when and how to invoke it.

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

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

Schema coverage is 100%, so the baseline is 3, but the description adds value by clarifying the behavioral difference between omitting the integration parameter and supplying one. It also reinforces the meaning of the own_* versus platform_* distinction, though the schema already documents the enum in detail.

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

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

The description states a clear onboarding purpose: explain Trickl integration choices when no integration is supplied, or return a concrete setup plan when one is given. It distinguishes itself from sibling documentation tools by framing itself as the starting point and by describing the plan contents such as keys, API calls, webhooks, and sandbox verification.

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?

"Start here" gives explicit usage guidance, and the description clearly explains the two modes: omit the parameter to explore choices, or provide an integration to get a tailored plan. It does not explicitly name alternatives such as read_doc or search_docs, so it falls short of the highest level of when-to-use 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 only declare readOnlyHint=true, and the description adds substantial behavior beyond that: result ordering, included payload data, the four-state delivery lifecycle, the retry schedule (nextRetryAt), and the recommendation to re-poll while PENDING/DELIVERING. It does not disclose any result-size limit or pagination for a tool that claims to show 'every' delivery, which is the one meaningful 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?

Front-loads what the tool returns and its ordering, then compresses state semantics into compact 'STATE = meaning' fragments. No filler sentences; each sentence conveys a distinct operational fact.

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 does the work of describing return fields (payload, receiver result, lastStatusCode, lastError, nextRetryAt) and state meanings, which is exactly what an agent needs. It stops short of stating whether the list is bounded or truncated, leaving a minor gap for a 'shows every delivery' tool.

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

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

Schema coverage is 100% and the single goalId parameter is documented as coming from create_test_goal. The description reinforces the sandbox-goal scoping but adds no format or provenance detail beyond the schema, 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?

Names a specific verb (shows/list) plus resource (webhook deliveries) and scopes it to a sandbox goal and a defined ordering (newest first). No sibling tool covers webhook delivery history, so an agent can distinguish it from get_goal or simulate_goal_event without reading schemas.

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

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

Explicitly tells the agent what to do with results ('Use lastStatusCode and lastError to debug the receiver') and what to do with in-flight states ('check again in a few seconds'), which is actionable when-to-use guidance. It also defines every terminal and pending state so the agent knows what an empty/failed result means.

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?

readOnlyHint=true already covers the safety profile, so the description's added value is disclosing the return shape: exactly one section, returned in full as Markdown. Since no output schema exists, that disclosure matters. It stops short of describing error behavior for invalid ids or any size/truncation 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?

A single sentence with no filler; the return shape is front-loaded and the id provenance follows immediately. Every clause carries 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?

For a one-parameter read tool with annotations declaring read-only behavior and a fully documented schema, the description covers what it does, what it returns, and how to obtain the id. Nothing essential to a correct call 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 the schema already gives an example id format, so the baseline is met. The description adds real semantic value by tying the parameter to its source tool (search_docs), telling the agent where a valid id comes from rather than leaving it to guess.

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 (returns one section of the Trickl docs) plus scope (in full, Markdown). Naming the id's provenance (from search_docs) makes it easy to distinguish from the sibling search_docs, which locates rather than retrieves.

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?

"by id from search_docs" establishes the required workflow: search first, then read by id. There is no explicit when-not-to-use clause or statement about what happens for an unknown id, but the usage context is clear for a single-param lookup tool.

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

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

With only readOnlyHint=false in the annotations, the description carries real weight: it discloses the two return values and their purpose, idempotency semantics, the public-https webhook requirement with concrete tunnel examples, and the crucial caveat that sandbox webhooks are real signed HTTP requests. That is exactly the beyond-annotation context an agent needs.

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

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

Four tight sentences, front-loaded with the action and endpoint, then returns, then idempotency, then the webhook constraint. Every sentence carries information the agent needs and nothing is repeated from 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?

No output schema exists, yet the description names both returned values and why they matter, and it flags the non-obvious sandbox webhook behavior and idempotency. For a 6-param mutation with only a single annotation, this is complete enough to call 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 coverage is 100%, so baseline is 3, but the description adds meaning on top: webhookUrl must actually reach the user's receiver via a tunnel, and externalCreatorId is the idempotency key. The remaining parameters are left to the schema, so it does not fully compensate for the interaction between externalCreatorId and idempotency.

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 ('Registers a seller (provider) under the test key') plus the endpoint POST /providers/register, and makes the sandbox scope explicit so it is distinguishable from any production provider tooling among the 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?

Explains that this is the prerequisite for creating goals (providerLinkCode is 'needed to create goals'), which implicitly routes the agent to create_test_goal, and notes idempotency on externalCreatorId so repeat calls are safe. It does not explicitly call out exclusions or name an alternative path, 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?

The description discloses the return format (section ids with snippets) and the degenerate-input behavior, adding real context on top of readOnlyHint=true. It omits ranking/matching semantics and any limits on result count, which matters since 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 dense sentences: purpose first, then the read_doc handoff and the empty-query fallback. No filler and nothing buried.

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 one-parameter read-only search with no output schema, the definition covers purpose, result shape, the follow-up tool, and the no-argument mode. An agent can invoke it correctly without opening anything else.

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 schema already supplies example queries, so the baseline is 3. The description adds meaning the schema lacks: an empty query returns the full table of contents, which is a behavioral contract for the parameter's default, not a restatement.

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 (keyword search) and resource (Trickl partner docs) plus the covered surface areas (platform API, webhooks, embed widget), which lets an agent tell it apart from read_doc and the goal/test siblings. The return shape (section ids with snippets) is named in the same breath.

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 next step to read_doc for reading a single section, and defines the zero-argument mode ('leave query empty for the full table of contents'). It does not state when NOT to search (e.g., when you already know the section id), so it stops just short of full when/when-not coverage.

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?

Beyond the readOnlyHint=false mutation flag, the description discloses that real signed webhooks fire to the seller's webhookUrl, the exact lifecycle effects per event (e.g., deposit paid triggers goal.deposit_paid plus goal.subscription_created for subscriptions), a specific failure mode (ALREADY_FUNDED when the current period is paid), and post-state ('the goal stays SAVING'). This is rich behavioral context an agent cannot get from annotations alone.

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 most important fact — instant lifecycle transition with real webhook delivery — is front-loaded, and every parenthetical carries event-specific detail. It is dense and somewhat run-on, but little could be removed without losing behavioral signal.

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 mutating simulation tool with no output schema, the description covers mechanics, per-event effects, failure modes, and sequencing. The one gap is what the call returns (e.g., resulting goal state or webhook delivery id), which would help an agent verify the simulation.

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 80%, but the description adds substantial meaning beyond the enum: it explains the consequence of each event value, clarifies the default $3 round-up chunk for collect, and notes when reversal=true selects the clawback path. This goes well past the terse schema field descriptions.

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

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

States a specific verb ('moves a sandbox goal through its lifecycle instantly') and resource, and immediately clarifies the key mechanic: each event sends the real signed webhook to the seller's webhookUrl. This clearly distinguishes it from siblings like create_test_goal and cancel_test_goal, which set up or tear down goals rather than driving them through lifecycle transitions.

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 per-event breakdown (confirm, collect, complete, payment_failed, expire) tells the agent which event maps to which real-world scenario, and 'Confirm first' gives explicit sequencing guidance. It doesn't explicitly state when *not* to use it versus alternatives, but the sandbox-simulation scope is unambiguous.

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