FundingTracker

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so safety and determinism are covered. The description adds that the content includes links to key public pages, which is mild extra context, but says nothing about output shape or length beyond the topic list.

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 front-loaded sentence enumerating the content scope, with no filler. The comma-heavy topic list is dense but each clause maps to real content coverage.

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, and the description compensates by enumerating what the result contains (product identity, audience, tracked data, plans, bank data/contracts, links). For a static no-param info tool this is largely sufficient, with only minor gaps about depth or formatting.

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?

Zero parameters, so the baseline of 4 applies. The description correctly implies no inputs are needed by framing the tool as a fixed informational resource.

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 the specific subject matter (what FundingTracker.app is, who it's for, what it tracks, plans, bank data and contracts handling, links to public pages). This is clearly distinguishable from the calculator/lookup siblings, though it never explicitly contrasts itself with them.

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 only implied: an agent can infer this is the orientation/overview entry point, but there is no explicit 'use this when' or 'use X instead' statement. The sibling list makes the alternative route (calculate_mca_apr, search_funders) obvious but the description doesn't say so.

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 read-only, idempotent, non-destructive safety, so the description correctly spends its words on methodology instead. It discloses the day-count conventions (21 business days/month, 252/year, 4.33 weeks/month) and the present-value discounting approach for APR, which materially affect results and are not in the schema. Minor gap: no note on rounding or how partial payment counts are handled.

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

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

Two sentences, front-loaded with the conversion and its outputs, followed by the calculation conventions that justify the results. Nothing is redundant, though the 'same formula as the FundingTracker MCA calculator' clause is the weakest use of space.

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?

An output schema exists and annotations carry the safety profile, so the description needs only to establish the conversion and its conventions — both done. The day-count and APR discounting disclosure is exactly the information an agent needs to trust and interpret the numbers.

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%, with bounds, examples and the factor-rate-to-payback relationship already documented per parameter. The description adds no parameter-level detail beyond that, 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?

States a specific verb and resource ('Convert a merchant cash advance factor rate') and enumerates the exact outputs: total payback, cost of capital, payment size, number of payments, effective APR. This clearly separates it from siblings like estimate_mca_payoff and mca_payment_impact.

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 only implied by the mention of the 'FundingTracker MCA calculator' formula, giving some context for when this tool is the authoritative source. However, there is no explicit when-to-use versus estimate_mca_payoff or mca_payment_impact, and no stated exclusions or prerequisites.

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 safe, read-only, idempotent calculation. The description adds useful behavioral context: the remaining-balance formula and the rule that daily payments skip weekends, which helps an agent trust the projection logic.

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 efficiently packed sentences; outputs are front-loaded and the calculation rule is appended without waste. No redundant or filler text.

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 calculator with an output schema and full parameter descriptions, this is nearly complete. Minor gaps remain around edge cases (e.g., amount_paid exceeding total payback or rounding), but the core behavior needed to invoke it correctly 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 description coverage is 100%, so all six parameters are already documented in the input schema. The description restates the key inputs and the total-payback relationship but adds little parameter-level detail beyond what the schema provides, fitting the baseline of 3.

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 ('Estimate') and names the exact outputs: remaining balance, payments left, and projected payoff date. This clearly separates it from siblings like calculate_mca_apr and mca_payment_impact, which address different questions.

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 explains what the tool computes but gives no guidance on when to use it versus alternatives such as calculate_mca_apr or mca_payment_impact. There are no exclusions or decision criteria for 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, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered and the bar is lower. The description contributes that the profile is 'public' and includes aggregate rating/review counts plus recent reviews, but says nothing about behavior for unknown slugs, pagination of reviews, or caching.

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 front-loaded sentence with the action and identifier first, followed by the returned fields. The trailing field list is slightly enumerative but every item tells the agent something it would otherwise have to guess, so nothing 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?

With no output schema, the description correctly spends its words describing the returned profile contents, and the single parameter is fully documented in the schema. Only the failure case (slug not found) is left unaddressed, which is a small gap for a read-only lookup.

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 slug parameter's schema text already gives the example format and the source (search_funders or the fundingtracker.app URL). The description only repeats the lookup key as 'slug' and adds no syntax or format detail beyond the schema, so 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 one funder's public profile from the FundingTracker directory') and adds the lookup key ('by slug'), which cleanly separates it from the sibling search_funders. It also enumerates what the profile contains, so an agent knows what it gets without opening the schema.

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

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

The phrase 'by slug' implies this is a follow-up detail fetch after a search, but the description never names search_funders or states an explicit when-to-use/when-not rule. Usage is inferable rather than stated, so it sits at the minimum-viable level.

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

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description's added value is the return shape: markdown text with canonical URL, takeaways, sections, checklist, and FAQs. This is meaningful disclosure beyond annotations, though it omits not-found or error behavior.

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 well-formed sentence that front-loads the action and enumerates the return contents without waste.

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 usefully enumerates what the response contains, which is exactly what an agent needs. Only gap is behavior on invalid or missing slug, which the annotations do not cover.

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 sole slug parameter is fully documented there, including the example and the source tool. The description adds no parameter meaning beyond the schema, 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?

States a specific verb (Return the full text) and resource (one FundingTracker MCA guide), which distinguishes it from the list-oriented sibling search_mca_guides by emphasizing a single guide. No explicit sibling naming, so it falls short of 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?

The description implies retrieval of a single known guide but gives no explicit when-to-use or when-not guidance. The routing hint (slug from search_mca_guides) lives only in the schema, not the description.

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 read-only, idempotent, non-destructive behavior, so the bar is lower. The description adds valuable behavioral context beyond annotations: the risk thresholds (30%+ high, 15%+ medium) and the fact that payment burden is normalized to a daily equivalent before comparison.

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 front-loaded sentence with no filler. Every clause contributes either the core measurement, an output field, or a decision threshold.

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 three-parameter read-only calculation with an output schema and full schema coverage, the description is nearly complete: it explains the calculation basis, normalized outputs, and risk thresholds. A minor gap is that it does not explicitly state the daily-vs-weekly conversion rule or business-day assumption, though the schema covers frequency.

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 all three parameters are already documented, including the daily/weekly enum. The description adds only marginal param-level meaning by implying weekly payments are converted to a daily-equivalent before ratio calculation; otherwise it relies on 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?

It uses a specific verb and resource ('Measure how heavy an MCA payment is against average daily revenue') and enumerates the exact outputs. It is clearly distinguishable from siblings like calculate_mca_apr (cost of capital) and estimate_mca_payoff (payoff timeline).

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

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

Usage is implied by the stated purpose and output fields, but the description never says when to choose this vs calculate_mca_apr or estimate_mca_payoff, nor does it state prerequisites or exclusions. An agent can infer the use case but is not explicitly routed.

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 read-only, idempotent, non-destructive, closed-world behavior, so the description's burden is lighter. The description adds useful context by identifying the directory as public and disclosing the exact return fields (slug, profile link, merchant review rating). It does not mention pagination or result-count behavior, but the schema covers the limit.

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

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

Two tightly written sentences, front-loaded with the core purpose, followed by return details. Every sentence earns its place and there is no 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?

With no output schema, the description compensates by naming the return fields, which is valuable for a search tool. It omits details like pagination or total-count behavior, but the schema already covers the limit parameter, leaving the definition complete enough for correct invocation.

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

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

Schema description coverage is 100%, so all three parameters are already well documented with defaults, ranges, and examples. The description reinforces the matchable fields and financing-type examples but adds little beyond the schema's own text, making the baseline 3 appropriate.

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

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

The description states a specific verb and resource ('Search FundingTracker's public directory of ... providers') and narrows the matchable fields (name, description, financing type). It clearly distinguishes itself from get_funder by framing this as directory search rather than single-funder retrieval.

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 clear context for when this tool applies (finding providers by name, description, or financing type) and notes that omitting the query lists the directory. It does not explicitly name the alternative get_funder for retrieving a full profile, so no exclusion guidance is present.

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

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so safety is covered. The description adds the return shape (titles, short answers, links) and frames it as a preview tier below full-text retrieval. It does not mention result ordering or relevance behavior, keeping it short of 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?

Two sentences, zero waste. The capability and topic scope come first, and the escalation path to get_mca_guide is placed last where it belongs.

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 naming the returned fields. For a two-parameter, zero-required search tool with full annotation coverage, nothing an agent needs in order to call 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%: both `limit` (1-20, default 10) and `query` (with examples and 'omit to list every guide') are fully documented in the schema. The description's topic list indirectly helps query formulation but adds no syntax or format detail beyond the schema, 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?

Specific verb plus resource ('Search FundingTracker's merchant cash advance guides') with an enumerated topic list that tells the agent exactly what content is indexed. It also states what comes back (titles, short answers, links), so the agent can distinguish it from get_mca_guide 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?

Explicitly routes the agent: use this for search, then 'call get_mca_guide for the full text.' That names the sibling and the condition that selects it, which is the main decision point an agent faces here.

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