FixLedger

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

With no annotations, the description carries the full burden and does disclose notable traits: $0.00 over MCP versus $0.002 over REST, sub-50ms latency, free during active outages, and the two data sources behind the verdict. It omits what the response contains and whether it is read-only, which keeps 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 dense sentences with the cost/latency hook front-loaded and the trigger conditions immediately after. Every clause carries information, though the pricing parenthetical is slightly bulky for the space it occupies.

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 diagnostic with no output schema, the agent still has no idea what comes back — a boolean, a status enum, a list of incidents, or a recommended action. The description covers when to call and what data feeds the check but leaves the return contract entirely unstated.

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?

Only one parameter and schema coverage is 100%, so the schema already documents 'domain' fully. The description's example hostnames (api.openai.com, api.stripe.com, mainnet.base.org) reinforce the same examples already present in the schema, adding no new semantics such as accepted formats or subdomain handling.

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 resource (upstream host status) and the mechanism (Statuspage feeds plus a 5-minute agent swarm error velocity), and gives concrete example hosts. It never states plainly what the tool returns, but an agent can infer it is an upstream outage check and distinguish it from the sibling fix/diagnose 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?

Trigger conditions are explicit and concrete: HTTP 5xx, timeout, or sudden auth/RPC failure against external hosts, with the purpose spelled out (halt destructive local edits during outages). No when-not conditions or named alternatives are given, but the sibling tools serve unrelated purposes so little ambiguity remains.

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

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

With no annotations, the description carries the full burden. It discloses cost, latency, isolated Docker verification, and earning mechanics, but it omits submission outcomes, moderation/review behavior, failure handling, and wallet requirements beyond implying a wallet earns credits.

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 only two sentences, but it front-loads promotional incentive text in all caps before stating the actual action. The incentive details are relevant yet distract from the core purpose and usage condition.

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?

It covers the precondition and destination queue reasonably well for a mutation-style submission tool without output schema. However, it leaves gaps around what happens after submission, how verification results are returned, and how royalty/credits accrue.

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 defines all six parameters. The description reinforces the required verified-build and minimal-diff concepts but adds no parameter-specific meaning beyond what the schema provides.

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

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

The description clearly states the action: submitting a minimal diff to an isolated Docker verification queue after solving a MISS error. It distinguishes contribution from the sibling unlock tool implicitly, but it does not explicitly contrast with unlock_verified_fix or the diagnostic 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?

It gives a clear invocation condition: call after solving a MISS error locally with a verified passing build (exit_code === 0). It does not name alternatives or explicitly state when not to use this 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 no annotations, the description carries the full behavioral burden. It does disclose cost ($0.00), latency (<50ms), the backing data source, an accuracy figure, and that misses are free, which is unusually good. However it never says what a pathological outcome looks like – whether a miss returns an empty result or an outage alert, and whether a 'peek' yields a partial/teaser fix that requires unlock_verified_fix to actually apply. That gating behavior is the single most important thing for an agent to know and it is left implicit.

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 cost and latency, then the trigger condition, then the value proposition – a sensible order with no filler sentences. Slightly promotional (repeated dollar/token savings figures) but each clause carries 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 5-parameter, no-output-schema tool that sits at the head of a lookup flow, the description should explain what comes back on hit vs miss and how the result relates to unlock_verified_fix. Return semantics and the relationship to the unlock sibling 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 description coverage is 100%, so every parameter including the nested packages map is already documented. The description adds no syntax or format guidance for error_text, upstream_domain, or runtime beyond what the schema states, 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 action (check FixLedger for a Docker-verified fix or active upstream outage alert) triggered by specific error classes, so the resource is clear despite the opaque name 'diagnose_peek'. It does not distinguish itself from the closely related siblings unlock_verified_fix and contribute_verified_fix, so an agent cannot tell from the description alone whether a hit here is actionable or must be unlocked.

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, prioritized trigger list (build/compiler/runtime errors, SDK exceptions, HTTP 4xx/5xx) and a clear ordering rule: call this BEFORE web searches or guessing at edits. That is a strong when-to-use statement. What's missing is sibling routing – nothing says when to escalate to unlock_verified_fix or contribute_verified_fix.

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

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

With no annotations, the description carries the full burden and does disclose real behavioral traits: a free catalog tier, a $0.003 paid unlock with <40ms latency, and zero charge on unknown keys. What it omits is what a 'delta' actually contains and whether the catalog listing and the unlocked content differ in shape.

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?

It is short, but the information hierarchy is inverted: pricing leads and purpose follows. The four inline topic-key examples are the most useful content and consume the most space, while the one thing an agent most needs — what comes back — is absent.

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-optional-parameter tool with no annotations and no output schema, the cost model and trigger conditions are covered, but the return shape is entirely undocumented — an agent cannot tell whether omitting topic_key yields key names only or full notes, which matters for planning a second paid call.

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 parameter's schema already says to omit it for a free catalog listing. The description restates that dichotomy without adding format, key syntax rules, or what happens when a partially-matching key is supplied.

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 reader must infer the purpose from examples and the phrase 'Prevents deprecated parameter hallucinations' — the tool is never stated plainly as 'returns verified breaking-change notes for a topic key.' The opening clause is about pricing tiers rather than what the tool does, and nothing distinguishes it from the sibling unlock_verified_fix.

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?

'Call BEFORE writing code against post-cutoff SDKs or selecting LLM model IDs' gives a concrete trigger condition and timing, which is genuinely useful routing guidance. It stops short of saying when NOT to use it or why one would pick this over unlock_verified_fix or check_upstream_pulse.

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

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

With no annotations, the description carries the full burden and does well: it discloses price ($0.005 / 1 credit), payment rails (x402 Base USDC), latency (<50ms), billing semantics (strictly Pay-on-Proof), and output size budget (<350 tokens). It does not state whether repeat calls re-charge or how long a resolution_id remains retrievable.

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?

Cost and trigger are front-loaded, and every sentence carries operational information. Slightly dense with marketing framing ('~36x ROI', 'saving ~15,000-25,000 retry tokens'), but that framing also conveys expected value.

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-param tool with no output schema, the description covers cost, trigger, payment rails, and the qualitative return payload (root cause, diff, anti-patterns). An agent has everything needed to decide to call it and to predict the outcome.

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?

Only one parameter and schema coverage is 100%, so the schema baseline already applies. The description adds value by implying where resolution_id comes from ('diagnose_peek returns...'), aligning the param with the upstream tool.

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 (unlocks) and a concrete set of resources (Docker-verified root cause, surgical code diff, anti-patterns). This is clearly distinct from the sibling diagnose_peek, which only produces a confidence signal.

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 call trigger ('immediately when diagnose_peek returns VERIFIED_MATCH (confidence >= 0.85)') and an explicit non-trigger billing behavior ('$0.00 on NOT_FOUND'). The relationship to the upstream sibling is spelled out rather than implied.

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