Measure statistical release timeliness and punctuality against an advance release calendar

baltor_statistical_release_timeliness

Measure statistical release timeliness and punctuality against an advance release calendar: lag from the end of the reference period, delay against the pre-announced date, announcement notice and declared maximum lags, per dataset and overall.

Files, names only

LICENSE 1.0 KB
SKILL.md 4.7 KB
contracts/input.schema.json 3.3 KB
contracts/output.schema.json 15.4 KB
examples/example.expected.json 4.4 KB
examples/example.input.json 1.7 KB
references/provenance.json 4.9 KB
scripts/tool.py 10.2 KB
verification/test_tool.py 11.0 KB

Full files in your harness.

What it takes and gives

Command: python3 -B scripts/tool.py < examples/example.input.json
Input fields: audit_date, releases
Test: python3 -B -m unittest discover -s verification -p 'test_*.py' -v
Files: SKILL.md, contracts/input.schema.json, contracts/output.schema.json, scripts/tool.py
Placed for: OpenCode

Limits and scope

Limits: This is a supporting calculation for SDG target 17.18 on caller-supplied calendar records, not an official compliance assessment under any dissemination standard. Maximum lags and notice periods are the caller's declared targets; the tool does not know which standard applies to which dataset, counts calendar days only, and does not judge release content, revisions or the times of day of publication.

Details

Kind: Skill
Licence: MIT
Declared effects: reads files, runs commands
Placed for: OpenCode
Source: docs/architecture/NORTH-STAR.md
Size: 9 files, 56.4 KB
Identity: baltor_statistical_release_timeliness
Version: 574c8708b258f3cae6a74cba5272554aa459d8ac3c3fa212985c47df95679192

The version is the SHA-256 of the item your harness downloads; every file in it names its own checksum.

Where it is shown

Dates, times and time zonesCorner cases

Related components

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