mirror of
https://github.com/affaan-m/ECC.git
synced 2026-08-24 00:12:25 +02:00
754b8dd76c
* fix: make the installer runtime pass strict supply-chain vetting
Remediate the four enterprise supply-chain vetting blockers from
affaan-m/ECC#2502 so the installer runtime (package.json + manifests +
scripts/lib/**) passes strict exact-pin evidence policy:
1. Remove the package.json `postinstall` lifecycle script (it only echoed a
post-install banner) and move that banner to an explicit opt-in
`npm run welcome` command. No install-time lifecycle script remains.
2. Exact-pin every dependency in package.json (dependencies + devDependencies)
to the versions already resolved in package-lock.json; no ^/~ ranges.
3. Replace non-ASCII characters on the installer runtime script/config surface:
em-dashes (U+2014) in scripts/lib/{path-safety,install-executor,
install/link-rewrite}.js comments and the two "Itô" (U+00F4) occurrences in
manifests/{install-components,install-modules}.json descriptions become
ASCII, so strict-surface Unicode scanners are clean.
4. Drop the bare `require("ajv")` from scripts/lib/install-state.js; the file
already carries a complete hand-rolled validator enforcing the same
schemas/install-state.schema.json (ecc.install.v1) constraints, so the
installer closure is dependency-free (zero non-builtin bare requires).
Refs affaan-m/ECC#2502
* fix: avoid unpinned welcome invocations
Signed-off-by: Samar Tomar <samar_tomar@hotmail.com>
* fix: validate translated skill frontmatter
Signed-off-by: Samar Tomar <samar_tomar@hotmail.com>
* fix: repair skill frontmatter YAML
Signed-off-by: Samar Tomar <samar_tomar@hotmail.com>
* fix: add MIT license to core skill manifests; pin verification-loop tsc invocation
* fix: preserve tsc/pyright exit status in verification-loop type-check (set -o pipefail)
* chore(deps): sync lockfiles with exact-pinned package.json
Regenerate package-lock.json and yarn.lock so the pinned dependency
specs are reflected in both lockfiles. npm ci and Yarn's --immutable
install now pass the sync check. The resolution tree is unchanged
(231 yarn resolutions, byte-identical set; zero npm transitive drift);
only the root descriptor strings move from ranges to the versions
already resolved in the committed lockfiles.
Addresses the Codex P1 on #2503.
---------
Signed-off-by: Samar Tomar <samar_tomar@hotmail.com>
Co-authored-by: Samarjeet Singh Tomar <samartomar@gmail.com>
2.6 KiB
2.6 KiB
name, description, license, metadata, tools
| name | description | license | metadata | tools | ||
|---|---|---|---|---|---|---|
| data-throughput-accelerator | Use when large data ingestion, backfill, export, ETL, warehouse loading, manifest catch-up, or table synchronization needs to become much faster while preserving data correctness. | MIT |
|
Read, Write, Edit, Bash, Grep, Glob |
Data Throughput Accelerator
Use this skill when the bottleneck is moving, transforming, or saving lots of data. The goal is not just speed. The goal is faster correct data landing in the right place with proof.
First Distinction
Separate these before optimizing:
- source extraction speed;
- network transfer speed;
- warehouse/load speed;
- transform speed;
- serving-table freshness;
- live tail growth while the job runs.
A pipeline can be "fast" and still appear behind if new data arrives faster than the final catch-up window.
Fast Path Heuristics
- Move compute to where the data already is.
- Prefer warehouse-native scans, joins, and appends for large landed files.
- Use manifests or checkpoints so completed files/partitions are skipped.
- Use partitioning and clustering that match the read and append pattern.
- Batch small files, requests, and writes.
- Make writes idempotent through unique keys, manifests, or replaceable staging.
- Keep raw, derived, and serving tables separately accountable.
Workflow
- Read the current source, target, and manifest contracts.
- Measure backlog: external files, manifest rows, raw rows, derived rows, min/max timestamps, and unprocessed counts.
- Run a safe catch-up or sample benchmark.
- Compare variants: batch size, worker count, warehouse SQL, file grouping, staging shape, and manifest update method.
- Promote only the fastest path that keeps counts and timestamps coherent.
- Codify the path as a CLI, scheduled job, workflow, or runbook.
- Rerun final accounting after the codified path executes.
Accounting Output
Use a hard accounting block:
Data throughput result:
- Source files discovered: 294
- Files processed this run: 294
- Raw rows added: 9,683,598
- Derived rows added: 8,917,585
- Remaining tail: 24 files at readback time
- Runtime: 38.7s
- Correctness gate: manifest counts and table max timestamps match
Guardrails
- Do not delete raw data to make a metric look better.
- Do not skip failed files silently.
- Do not mix historical backfill status with live-tail freshness.
- Do not call a pipeline complete until the target tables and manifest agree.
- For finance, healthcare, regulated, or customer-impacting data, preserve replay evidence and approval gates.