Update to DSIR SDG Data Skill

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README.md

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 # DSIR SDG Data Skill
 
-Use natural language to discover and retrieve United Nations Sustainable
-Development Goal data. Powered by the data-access and cleaning logic developed
-in the DSIR R package. Users do not need R or DSIR.
-
-The skill retrieves public observations from the UN SDG Global Database. It
-supports health questions and other SDG topics represented in that database.
-It does not query WHO GHO, private WHO data or unrelated data sources.
-
-## Examples
-
-- Compare historical UHC service coverage in China, Japan and the Philippines.
-- Get tuberculosis incidence in the Philippines since 2015 from UN SDG.
-- Show maternal mortality ratios for Japan since 2000.
-- Find the SDG series for under-five mortality rates, both sexes.
-- What financial protection measure is currently published under SDG 3.8.2?
-- Find the measles second-dose vaccination coverage series.
-- Compare safely managed drinking water in urban and rural areas of the Philippines.
-- Does UN SDG publish UHC service coverage for the WHO Western Pacific group?
-
-The agent checks the live indicator AND series catalogues, resolves locations,
-retrieves all pages, keeps population dimensions and units, performs basic QA,
-and produces source-linked results with CSV and JSON downloads. It asks when
-different interpretations would materially change the answer.
-
-## Requirements
-
-- A compatible agent that can load a skill or skills-only plugin.
-- Python 3.10 or later in the agent execution environment, with standard-library
-  script execution. No third-party runtime packages are required.
-- Script HTTPS access to `unstats.un.org`, including the UN SDG V5 endpoint.
-- A writable output directory.
-
-No R, MCP server, remote service, Azure deployment, API key or end-user data
-download is required. The agent runs the bundled helpers. Installation alone
-does not grant network permissions or a script runtime; a web-search tool and
-the script runtime can have different access rules.
-
-## Packages and installation
-
-- `dsir-sdg-plugin-0.1.0.zip`: plugin upload/distribution artifact with manifest,
-  icons and the complete runtime skill. Use this in a supported **plugin upload**
-  or publishing workflow; do not treat a normal chat attachment as installation.
-- `dsir-sdg-0.1.0.zip`: standalone skill. Extract and place the `dsir-sdg` folder
-  (containing `SKILL.md`, `scripts`, `references`, and `agents`) in the host's skill
-  directory. For local Codex, use `~/.agents/skills/dsir-sdg/`. File Explorer is
-  sufficient on Windows; PowerShell is optional. Start a new conversation.
-- `dsir-sdg-0.1.0-source.zip`: maintainer source, tests, R parity harness, recorded
-  validation results and reproducible packaging code. R is used only by the
-  maintainer parity tests and is excluded from the runtime packages.
-
-In local Codex, ask: `Use $dsir-sdg to retrieve Philippine TB incidence since
-2015 from UN SDG.` In ChatGPT accounts where the plugin has been made available,
-install it from Plugins, start a new chat, select it with `@`, and ask naturally.
-Public listing or workspace distribution is a separate process. This build does
-not publish, register a marketplace, or install into an account. Account and
-workspace availability must be tested on the actual receiving account.
-
-## Local developer check
-
-From the skill directory, with Python 3.10+:
-
-```text
-python scripts/cli.py doctor
-python scripts/cli.py search "TB incidence"
-python scripts/cli.py describe 3.3.2
-python scripts/cli.py get 3.3.2 --locations PHL --year-from 2015 --output-dir outputs/tb-phl
-```
-
-Choose a new output directory on each run. Read `response.json` for the full
-answer and provenance, and share `observations.csv` for a table that retains
-dimensions and units. `dsir_clean.csv` reproduces DSIR's 15-column core and is
-intended for parity/interoperation. `raw.json` and `manifest.json` support audit.
-
-## Meaning and limitations
-
-Data source is **UN SDG**, even where WHO is the custodian. UN and WHO GHO releases
-can differ. The live catalogue may revise series names, definitions and codes.
-In the release checked in September 2026, UHC is labelled 2025 methodology, and
-SDG 3.8.2 uses 40% of discretionary household budget. This is not interchangeable
-with older 10%/25% total-expenditure measures.
-
-WHO regions and UN geographic regions are different. The live UN catalogue
-contains WHO Western Pacific, but area-catalogue presence does not guarantee
-observations for every indicator. No regional average or membership history is
-calculated. Missing/censored values remain missing/censored; no imputation,
-charts or models are included.
-
-The UN service may be slow or temporarily unavailable. Incomplete retrieval
-returns a distinct error, never a successful partial table or a claim that the
-UN lacks the requested data. Large global queries can exceed bounded limits;
-narrowing the geography reduces work. All-year retrieval precedes year and
-series filtering to preserve the DSIR endpoint workaround.
-
-## Validation and maintenance
-
-The source package contains `tests/`, `evals/`, `docs/source_audit.md`, and
-`reports/VALIDATION.md`. Evaluation includes live catalogue checks, explicit
-failure/empty-result tests, original-R parity and independent agent rehearsals.
-Automated casebook contracts are not a general language-model accuracy score.
-
-From the source skill directory:
-
-```text
-python -m unittest discover -s tests -v
-python evals/run_parity.py --live-r
-python packaging/build_release.py
-```
-
-Inspect `evals/README.md` for casebook commands and report meanings. R parity
-requires the maintainer's DSIR reference source; normal use does not.
-
-Official resources:
-
-- UN API: https://unstats.un.org/SDGAPI/swagger/
-- UN metadata: https://unstats.un.org/sdgs/metadata/
-- Plugin packaging: https://developers.openai.com/plugins/build/plugins
-- Plugin publishing: https://developers.openai.com/plugins/deploy/submission
+Find United Nations Sustainable Development Goal indicators and statistical series, then retrieve observations by country or region, year and verified population dimensions. Check the exact series definition and units before comparing values. Review source metadata, tables, suitable charts and findings calculated in code, or request a concise answer or files only. Export CSV and JSON with source details and completeness checks. Results remain attributed to the UN SDG database, including where WHO is the custodian; other sources are not silently substituted. Runs in ChatGPT Work using the host's script environment and public HTTPS access. Users do not install R, DSIR or additional packages, and no API key is needed. Independently maintained by Shanlong Ding.
 
-This is a personal DSIR project by Shanlong Ding, not an official UN or WHO service.
+## Using the plugin
+
+Enable the plugin in ChatGPT Work, select it with @, and ask a data question. The host supplies script execution and HTTPS access. No local environment installation is required. A host that cannot execute the bundled client cannot retrieve data; report that limitation.
+
+Request CSV and JSON downloads when needed. Keep units, dimensions, observation years, source and retrieval metadata with exported values. An empty result or request error is not a measured zero.
+
+## Candidate identity
+
+BUILD.json records the version, source commit and runtime file hashes. This archive is a release candidate for draft validation. Building or uploading it does not submit it for review or publish it.
+
+Add explicit UN SDG source boundaries and an adaptive metadata, table, visualization and findings template. Preserve the existing query runtime and exports. Clarify series definitions, units and comparability. Shorten the listing subtitle and update the cat icon.
+
+Software is MIT licensed. Source data remain subject to their original providers' terms.