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industrial-aiops

OT-AIops Energy

historian_coverage

Read-only

Assess historian data availability per tag: rows, first and last timestamps, to answer root cause analysis questions. Read-only and bounded, returns tag list with coverage details.

Instructions

[READ][risk=low] Per-tag history coverage — what history do we actually have.

Answers the question every RCA starts with: which tags have stored history,
how many rows, and over what time span — per tag {rows, first_ts, last_ts}
from the same store historian_push writes. Read-only, bounded (tag list is
capped with a truncation flag); no device I/O.

Args:
    reader: 'sqlite' | 'tdengine' | 'iotdb'. Omit to use the per-site
        'historian:' block in ~/.iaiops/config.yaml, else the local sqlite
        store. TSDB readers need their extra: pip install iaiops[tdengine|iotdb].
    limit: Max tags returned (1..2000; default 500).

Returns dict: {reader, source, tag_count, tags:[{tag, rows, first_ts,
    last_ts}], truncated} plus the standard return envelope
    (items_returned, items_total, items_total_is_exact, is_truncated,
    truncation_note).

Example: historian_coverage().

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
readerNo
Behavior5/5

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

The description discloses key behaviors beyond annotations: 'Read-only, bounded (tag list is capped with a truncation flag); no device I/O' and 'TSDB readers need their extra: pip install iaiops[tdengine|iotdb]'. It also explains fallback behavior for the reader parameter. These details add significant context that the annotations (readOnlyHint, destructiveHint) only partially cover.

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?

The description is well-structured with clear sections: a lead summary, Args, Returns, and Example. It is detailed yet concise, with every sentence contributing useful information. The use of headers and inline code makes it easy to scan.

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?

Despite having no output schema, the description fully specifies the return structure: '{reader, source, tag_count, tags:[{tag, rows, first_ts, last_ts}], truncated}' plus the standard envelope. It also provides an example call and covers optional dependencies, making it complete for the tool's moderate complexity.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by explaining both parameters: reader accepts 'sqlite' | 'tdengine' | 'iotdb', with default behavior (config or local sqlite) and pip install prerequisites; limit is 'Max tags returned (1..2000; default 500)'. This is thorough and adds meaning beyond the raw schema.

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 clearly states the tool's purpose: 'Per-tag history coverage — what history do we actually have.' It specifies the exact resource (history store) and the output (rows, first_ts, last_ts per tag). This distinguishes it from sibling tools like historian_query and historian_push by focusing on coverage metadata rather than data retrieval or writing.

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

Usage Guidelines4/5

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

The description provides strong context for when to use the tool: 'Answers the question every RCA starts with' and explicitly notes it queries the same store historian_push writes. However, it does not explicitly name alternatives or describe when not to use it (e.g., 'for actual data values use historian_query'), so it falls short of a 5.

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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