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SigRank — AI Operator Benchmarking

Export SigRank Standard Record

get_sigrank_standard_record
Read-onlyIdempotent

Build a SigRank Standard v0.1-draft portable operator record from available token telemetry. Input and output are required; unavailable cache telemetry remains null. Computes only the five-metric portable core through @sigrank/cascade and does not submit or persist data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolNoOptional tool/client identifier.
inputYesFresh input tokens.
modelNoOptional model identifier.
outputYesOutput tokens.
providerNoOptional provider identifier.
timestampNoOptional ISO-8601 timestamp. Defaults to the current time.
cache_readNoCache-read tokens, or null when unavailable.
cache_writeNoCache-write / cache-creation tokens, or null when unavailable.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
specYes
sourceYes
metricsYes
warningsYes
telemetryYes
timestampYes

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that unavailable cache telemetry remains null, that the computation is limited to the five-metric portable core via @sigrank/cascade, and that no submission or persistence occurs. This meaningfully clarifies side effects and null-handling behavior without contradicting the readOnly/idempotent annotations.

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

Conciseness5/5

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

Two dense sentences carry all key information with no filler. The most important facts — purpose, required fields, null behavior, computation scope, and non-persistence — are front-loaded and each earns its place.

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

Completeness5/5

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

Given the rich annotations, full schema descriptions, and presence of an output schema, the description covers everything an agent needs to select and invoke the tool correctly. It adds version specificity and side-effect guarantees that round out the context.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents all 8 parameters. The description adds useful context about required input/output and null cache telemetry, but most parameter meaning is already available in the input schema, so the incremental value is moderate.

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

Purpose5/5

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

The description names a specific verb ('Build'/'Export') and resource ('SigRank Standard v0.1-draft portable operator record') and clearly ties it to token telemetry. It also distinguishes itself by stating it 'computes only the five-metric portable core' and 'does not submit or persist data', which separates it from sibling tools.

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

Usage Guidelines3/5

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

The description gives clear operational conditions: input and output are required, cache telemetry can be null, and the tool is non-persisting. However, it does not explicitly say when to prefer this tool over siblings or name alternatives, so the usage guidance is mostly implied rather than explicit.

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

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TDQS

B3.4/5.0
Disambiguation2/5

Several tools have significantly overlapping purposes: benchmark_me and compare_to_field both compare a user's cascade to the field, operator_signature and who_operates_like_me both find comparable operators, and rank_paste/rank_windows overlap as metric calculators. Descriptions clarify the output format, but an agent would frequently struggle to pick the right tool.

Naming Consistency3/5

All names are lowercase snake_case, which is readable, but the pattern is mixed: get_leaderboard and simulate_change are verb-first, field_anomaly and operator_gap are noun-first, and rank_if, rank_paste, benchmark_me, and who_operates_like_me break the convention entirely. There is a loose semantic system, but no strong predictable verb_noun pattern.

Tool Count3/5

16 tools sits right at the heavy borderline, and the count feels inflated by overlapping tools that could be consolidated. The domain is broad enough to justify more than a handful of tools, but the duplication makes the set feel heavier than its actual functional surface.

Completeness4/5

The tool set covers the core benchmarking workflow well: reading leaderboard/operator data, computing metrics, comparing to the field, diagnosing weaknesses, simulating changes, and suggesting improvements. There are minor gaps, such as no way to retrieve a user's raw token pillars from a codename for simulation tools that require four pillars, but these are workable.