AllClear Lending

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered; the description still adds real value by stating this produces an estimate and never an offer, and by noting inputs are categorical answers with optional rounded figures. It does not cover return shape beyond 'program TYPES', but the non-commitment caveat is the key behavioral fact for this domain.

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?

Dense but efficient: one purpose sentence, one disclaimer, then two tight per-lane value inventories with all keyword noise removed. The opening 'Lane PC ... or BC ...' fragment is a slightly awkward lead, but nothing is repeated or 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?

With no output schema, the description must describe returns and does so in outline (program types, plain descriptions, typical ranges) while fully documenting the nested answers object. Remaining gaps are modest: what the ranges measure (rate, amount, term), and what happens if answers from the wrong lane are supplied.

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 0% and the schema itself is a permissive object with only a maxLength constraint, so the description carries the entire burden and does: it enumerates the exact allowed values for every PC answer (deal, occupancy, owner, propertyType, experience, exit) and every BC answer (timeInBusiness, nsf, openPositions, use), and marks which keys are optional numeric figures. This far exceeds what the input schema conveys.

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 second sentence gives a specific verb and resource: returns program TYPES with plain descriptions and typical ranges from categorical answers. That distinguishes it from find_lenders (a directory lookup) and lender_program (a single program detail). The opening lane abbreviation fragment is more parameter preamble than purpose statement, so the core is clear but not perfectly front-loaded.

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 never says when to call this instead of find_lenders, lender_program, or next_best_option, nor does it state prerequisites such as call order or what to do if the user's lane is unknown. The only usage-adjacent statement is the disclaimer 'An estimated match, never an offer', which sets expectations rather than routing the agent.

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 is covered; the description adds real value beyond that by disclosing the ranking rule (cheapest-suitable first), the exact result fields (institution, program, products, geography, broker path, submission channel, source URL), and the "not an offer; lenders decide" caveat. It omits result-count behavior and the default limit, which is why it is not a 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 dense sentences with the resource and ranking rule front-loaded, the return shape second, and the disclaimer last. No filler, no restatement of the title.

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 an 8-parameter read tool with no output schema, the description compensates well by enumerating the returned fields and explaining the sort order. The remaining gap is operational: nothing about the limit default or maximum, and nothing about how many lenders are typically returned.

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 75%, so much of the parameter meaning is already structured. The phrase "for the bands given" is the only added semantics, hinting that amount, credit, and tenure bands drive suitability ranking rather than simple filtering, but it never says which bands affect rank, what an omitted band defaults to, or how citizenship interacts with program eligibility.

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?

"Named lenders and programs for an industry, optionally filtered by state and product and ranked cheapest-suitable first" gives a concrete resource, its scope, and the ordering rule, so the agent knows this is a curated lender lookup rather than a calculator or a program-detail tool. It stops short of naming which sibling (estimate_match, lender_program, industry_overview) covers the adjacent job, so the separation is inferable rather than stated.

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 establishes the usage shape through "optionally filtered by state and product" and "for the bands given," telling the agent that only industry is mandatory and everything else narrows or ranks. There is no explicit when-to-use vs when-not guidance, no pointer to estimate_match or next_best_option, and no statement of what happens when no state or band is supplied.

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 in annotations, the description defines the expected qualitative output, such as providing ease tier classifications (A-D) and the 'dignity fallback.' This context is critical for an agent determining the depth of the report it is receiving.

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 concise and direct, functioning as an effective list of deliverables for the tool. It avoids fluff while effectively summarizing complex data fields.

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 holistic and complex nature of the report generated, the description is nearly exhaustive, providing a detailed map of all available information (e.g., SBA eligibility, white space) without requiring an output schema to be defined.

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?

Since the schema coverage is 100%, the baseline is 3. The description uses the parameters (industry, state) as context for the report rather than adding new semantic value beyond the input structure.

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 that the tool generates a comprehensive lending overview report for a single industry and defines all the specific data points contained within that report.

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 implies that this tool should be used when a broad, strategic market assessment is needed due to the wide range of data provided. However, it does not explicitly advise agents on when to prefer this over specific search-based siblings like find_lenders.

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 the safety profile is covered. The description adds that the result is the full public record, and implies a single record for id versus a collection for institution. It says nothing about response shape, empty results, or what 'public' excludes.

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, front-loading the resource and then the two access paths. Slightly awkward as a noun phrase rather than a clause, but every element 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 simple read-only lookup with full schema coverage and no output schema, the description conveys what is returned and the multiplicity difference between the two modes. It is largely complete, though it could say more about the record's contents or how to handle an unknown institution.

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 are documented there, including the 'if no id' fallback already stated in the institution field. The description adds only the provenance detail that ids come from find_lenders, which is marginally beyond the schema but not substantial. Baseline 3 for a fully described 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 names a specific resource (a lender program's full public record) and both retrieval modes: by program id, or all programs of one institution. It clearly distinguishes itself from find_lenders, which it positions as the source of ids. It stops short of a crisp verb, reading more as a noun phrase, which keeps it from 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 tells the agent the two entry conditions: an id obtained from find_lenders, or an institution name when no id is available. That implicitly routes discovery work to find_lenders. There is no explicit statement of when not to use it or how it differs from lender_stats, 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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are covered; the description adds real value on top with the k-anonymity suppression rule (a cell appears only with 5+ outcomes or when you reported into it) and the provenance caveat that figures come from reported outcomes rather than predictions. That suppression rule materially changes how an agent must interpret sparse or empty results, which is exactly the kind of trait the schema cannot express. It stops short of 5 because it does not say what an empty response means versus a suppressed cell.

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 waste: metrics first, dimensions second, the disclosure constraint third, then a one-line caveat. The k-anonymity rule is front-loaded before the agent could misread a missing cell as zero.

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, five-optional-parameter statistics tool with no output schema and no required arguments, the definition covers what is measured, how results are sliced, and why data may be withheld. Remaining gaps are how multiple filters combine and what an empty or suppressed result looks like, which are minor given the absence of an output 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 only 40%, so the description has to compensate: program_id, institution and reporter_key are undocumented in the schema. The description names program, institution, industry and state, giving meaningful mapping for four of five parameters, but it never clarifies whether these act as filters or as group-by axes, and it omits reporter_key entirely despite that being the key that unlocks small cells.

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 the exact metrics returned (approval rate, funded rate, median days to decision) and the grouping dimensions (program, institution, industry, state), which distinguishes it from siblings like report_outcome or find_lenders. It never explicitly names an alternative, so it falls short of the top band, but the resource and output are 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?

"From reported outcomes" and "counts of decisions, not predictions" imply this is the aggregate/retrospective view rather than a forecasting or lookup tool, which nudges the agent away from next_best_option. However, there is no explicit when-to-use or when-not-to-use statement and no routing to find_lenders, industry_overview or lender_program, leaving the choice 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=false, so the safety profile is covered; the description adds genuinely new behavior: results are ordered cheapest-first and guaranteed non-empty ('never a dead end'), with a floor of free nonprofit credit counseling. It does not disclose the shape of each returned option, which would have completed the picture.

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 dense sentence with the core mechanic front-loaded and the ordering constraint stated before the fallback floor. The 'rungs'/'decline-with-dignity' phrasing is colorful but costs little and 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?

No output schema exists, yet the description never says what a returned option looks like (program name, why it fits, cost), so the agent cannot anticipate the response. For a 7-parameter recommendation tool this is adequate on intent but incomplete on payload.

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 only 29% (state and industry are documented, the five enum parameters are not), so the description carries most of the burden. It offers only 'optional profile bands' as a hint that the extra parameters are optional narrowing filters, with no explanation of how any band affects the waterfall.

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 transformation: given a decline reason, return the next options to try, ordered cheapest-for-the-owner first and ending at free nonprofit credit counseling. An agent can distinguish this from find_lenders or estimate_match because it is explicitly a post-decline recommendation waterfall, not a lender lookup or match score.

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 'given why a business was declined' framing implies the trigger condition (use after a decline) but never states when to use this versus find_lenders or estimate_match, nor any exclusions. Usage is inferred rather than directed.

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?

Adds real value beyond the annotations: the privacy constraint that only bands and no names/amounts/identifiers may be submitted, the reciprocity gating of lender_stats, and the reporter_key/header convention. However, annotations declare idempotentHint=false, and the description never warns that re-submitting produces a duplicate outcome, nor does it state what is returned after a successful write. That missing non-idempotency warning is the main behavioral 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?

Four tight sentences, front-loaded with what is added, then the privacy rule, then the incentive, then the key convention. No filler and nothing restated from the schema 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?

For a 14-parameter write tool with no output schema and thin schema coverage, the description covers the two things an agent could get wrong dangerously (identity leakage in free-text fields, unstable reporter_key). It does not cover return behavior or duplicate-submission risk, which is a modest remaining gap rather than a blocking one.

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 only 29% across 14 parameters, so the description must compensate. It does convey the central semantics — all quantitative fields are bands, free-text must not contain identifiers, and reporter_key is a stable per-reporter credential (also accepted as an X-AllClear-Key header). But it says nothing about how program_id and institution relate, which of the many enum fields matter for which decision, or when decline_reason_code applies, leaving most low-coverage params undocumented.

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 ('add one submission outcome to the shared outcome graph') plus the exact shape of what is reported: lender, band-level file characteristics, and decision. The '(bands only)' qualifier and the 'no names, amounts or identifiers' clause make it unambiguously distinct from the read-side siblings like lender_stats and find_lenders.

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 reason to call it — reporting unlocks lender_stats for the cells you report into (give-to-get) — and a repeated-use rule ('pass the same reporter_key each time'). It does not name an alternative or a when-not-to-use condition, but no sibling performs a write so there is little to route 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 already declare readOnlyHint=true and openWorldHint=false, so the bar is lower, yet the description still adds real value: it discloses which states are actually researched versus which silently degrade to general notes, and it flags the output as research notes rather than legal advice. That coverage/fidelity disclosure is exactly the kind of behavior an agent needs and cannot get from the annotations. It does not describe response size or freshness of the research, which keeps it at 4.

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 payload is front-loaded in a single sentence that leads with the value proposition, followed by two short fragments for coverage and disclaimer. Almost every element earns its place, though the lane list and field list make the first sentence dense and slightly scannable-poor. No filler or 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?

There is no output schema, and the description compensates by enumerating the returned components (status, rule, gate, open counsel questions, sources). Combined with the researched-state coverage statement and the not-legal-advice caveat, an agent knows what to send, what it will get back, and how to weigh it. Nothing material is missing for a one-parameter read 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 'state' parameter is documented as a two-letter code, so the schema carries the parameter burden. The description adds one piece of semantic meaning — that non-researched state values still return something (general notes) rather than erroring — but gives no hints about accepted casing or full names. 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 concrete resource — state brokering rules broken out by lane (investor real estate, consumer, working capital, SBA, cards) — and enumerates the fields returned (status, rule, gate, open counsel questions, sources). That is far more specific than the title alone, and the subject matter (state-level regulatory rules) naturally sets it apart from the lender-oriented siblings. It stops short of explicitly contrasting itself with any named sibling, so a 4 rather than 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?

Usage is implied: an agent can infer it is the tool for state-specific brokering compliance questions. The description does add a useful boundary — six researched states, with all others falling back to general notes — but it never states when to prefer this over siblings like lender_program or industry_overview, nor any prerequisites. Adequate context, no explicit routing.

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