failecho

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

No annotations are provided, so the description carries the full burden and does: read-only, free, anonymous, unauthenticated, never rate limited, stores nothing, plus null-recommendation semantics, Wilson-score confidence provenance, demo_data_included, and evidence_sources weighting. This is unusually complete disclosure for a tool with zero annotation coverage.

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

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

Front-loaded with the trigger and the pre-retry rule, then structured into behavior and return-field paragraphs, all of which are substantive. It runs long, and the return-value paragraph partly duplicates an output schema that already exists, costing it the top mark.

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 8-parameter, evidence-interpretation tool with an output schema; the description supplies the interpretive context an agent needs (what HEALTHY/DEGRADED mean, when recommendation is null, how to weigh first_party vs agent sources) rather than relying on raw fields. Nothing needed 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 description coverage is 100% and the parameter docs are detailed (naming conventions, redaction, schema_hash purpose), so the schema already does the heavy lifting. The description itself adds almost nothing about parameters beyond reinforcing 'service + operation' — 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 ('check whether other autonomous systems recently experienced the same failure' and return failure intelligence), and its 'reading is free... stores nothing' framing implicitly separates it from the report_* siblings, which are writes. An agent can tell what this does 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?

Explicit trigger ('when another tool, API call, or MCP server operation fails'), explicit ordering ('call it BEFORE retrying'), and an explicit alternative — blind retry — with the condition that makes skipping it correct. Nothing about when to invoke is left 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?

With no annotations, the description carries the full behavioral burden, and it delivers: it discloses that reports feed downstream recommendations, that each attempt should be reported separately, and that contributions are rate-limited per action. It also frames the tool as telemetry, which makes the side effect of calling it clear.

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 front-loaded with the tool's purpose and remains focused: the first sentence states exactly when to call it, and later sentences justify the telemetry value, enumerate common actions, and set rate expectations. It is longer than a minimal description, but the added sentences all carry operational guidance rather than 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?

For a four-parameter telemetry tool with full schema coverage and an output schema, this description is complete: an agent knows when to call it, what to pass, what action values exist, how to avoid duplicate reports, and the rate limit. The only minor omission is an explicit alternative to report_tool_success, but that does not block 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 coverage is 100%, so the baseline is 3; the description adds value above the schema by listing canonical action values, explaining that the fingerprint must come from check_tool_failure or report_tool_failure, and linking the action parameter to per-hour confidence accumulation. It does not duplicate parameter formats, letting the schema handle syntax.

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 and resource: it instructs the agent to report whether a recovery action resolved a known failure, and it ties the report to a fingerprint from check_tool_failure or report_tool_failure. This clearly differentiates the tool from the sibling failure-reporting tools: check/report_tool_failure record the failure itself, while this records the outcome of the attempted 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?

It specifies the exact trigger ('After you acted on a known failure'), what to pass (the fingerprint), and common action values to report. It also sets rate and granularity guidance ('one outcome per attempt', 'at most 5 attempts per hour'), though it does not explicitly state when to prefer report_tool_success over 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 and does so well: it discloses anonymous public contribution, server-side normalization of error text, discarding of raw text, salted-hashed reporter_id storage, per-client rate limits, and what must never be sent. These are exactly the traits an agent needs before invoking a write to a shared network.

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 purpose, then usage, then privacy, then parameter notes — a sensible order. The privacy paragraph is long but each clause (banned categories, server-side normalization limits, the 'safety net, not a licence' caveat) earns its place; still, the block could be tightened.

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

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

9 parameters, 2 required, an output schema present (so return values need no explanation) and no annotations — the description fills the gaps that matter: privacy boundaries, rate limiting, normalization behavior, and the identity semantics of reporter_id. An agent has everything needed to call this correctly.

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

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

Schema description coverage is 100%, so the baseline is 3; however the description adds meaning beyond the schema by explaining the purpose of reporter_id (salted/hashed, counts you as one independent reporter rather than anonymous noise), the normalization applied to error_message, and the privacy constraints on all fields.

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 (anonymously contribute) and resource (a tool/API/MCP failure to FailEcho) plus the benefit to other agents. It is clearly separable from the sibling check_tool_failure, which it names as a companion query rather than a duplicate.

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 trigger is explicit: 'Call this whenever a tool call fails, after (or alongside) check_tool_failure.' That gives a clear condition and ordering relative to one sibling, but it never states when NOT to use it or how it differs from report_tool_success / report_recovery_outcome, so the routing guidance is incomplete.

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 and does real work: it declares the call is cheap, carries no error payload, transmits metadata only, and never sends arguments or results. It omits auth/permission requirements, idempotency or duplicate-report behavior, and any rate-limit context.

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

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

Front-loaded with the action, then rationale, then payload/privacy constraints — a sensible order. The middle sentence is somewhat discursive ('This matters more than it sounds...'), but it earns its place by justifying the tool's existence.

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, so return values need not be described, and the privacy boundary (metadata only, never arguments or results) is stated explicitly. For a 6-parameter telemetry write tool with no annotations, the description is nearly sufficient; only permission/rate-limit behavior is unaddressed.

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 documents all six parameters including naming conventions and hashing. The description's summary of what is carried (service/operation/version/latency) adds only framing, not new parameter semantics. 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 ('Report that a tool call SUCCEEDED'), which is directly distinguishable from the siblings report_tool_failure and check_tool_failure. An agent can pick this tool 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 explanation of why success reporting matters (failure rate is failures/total, so failure-only reporting produces wrong statuses) effectively tells the agent to report on success, not just failure, which is the key routing decision against its siblings. It stops short of an explicit 'call this after every successful call, including on retries' rule or naming the sibling tools.

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