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implementation-pack

implementation-pack

github.com/gasseraneProductivity3551 installsUpdated 6d ago
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About implementation-pack

A skill that generates an IPPF-branded implementation pack for project managers after an award. It loads a donor profile and proposal baseline, applies awarded figures when provided, and builds a standalone pack without requiring AI to run it.

Key features

  1. 01Load donor reporting settings
  2. 02Use a proposal baseline
  3. 03Apply awarded budgets, dates, and targets
  4. 04Build a project implementation pack
  5. 05Mark fields for project-manager completion

Use cases

  1. 01Prepare a pack after a project award
  2. 02Turn a proposal baseline into delivery materials
  3. 03Update targets from a signed grant agreement

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/gasserane/personal-skills --skill implementation-pack

After installing, type/implementation-packin Claude Code to confirm it loaded.

Details

From the project README

/implementation-pack — post-award PM pack generator

You generate a standalone, IPPF-branded implementation pack a full project manager runs with no AI dependency. You are the front-half: load baseline, apply awarded figures, build. Vi executes any optional reporting spawns.

Arguments

  • --donor <name> (default cerv). Maps to ane_package/proposals/donor_profiles/<name>.json.
  • Optional baseline path (a proposal handback.json or a proposal pack folder).

Step 1 — Load the donor profile

from ane_package.proposals.config import load_profile
profile = load_profile("cerv")  # or the --donor value

State the implementation config back to Ane: reporting periods, RAG thresholds.

Step 2 — Load the baseline (never invent)

from ane_package.proposals.baseline_io import load_baseline
baseline = load_baseline(handback_path_or_dict)

If no baseline is available, ask Ane for the proposal handback or a baseline brief. Do not invent any WP, indicator, figure, or partner (factual-reliability rule).

Step 3 — Apply the awarded figures

Ask Ane for the signed grant-agreement budget, dates, and revised targets.

from ane_package.proposals.baseline_io import apply_awarded
baseline = apply_awarded(baseline, awarded)   # raises BaselineError on unknown WP/indicator or incoherence

If the project is not yet awarded, skip this step; the pack flags "baseline = submitted" in the Guide and README.

Step 4 — Build the pack

from ane_package.proposals.implementation_pack import build_implementation_pack
manifest = build_implementation_pack(profile, baseline, out_dir)

Apply mel_wiki/wiki/concepts/edit-preservation-protocol.md when target file exists — if the output folder already holds an edited pack, treat Ane's content as canonical and edit scope-bounded, do not regenerate from scratch.

Step 5 — Optional reporting cycle (only when Ane asks for a populated report)

Delegate to Vi to spawn mel-report-writer (draft the narrative from tracker status) and contribution-plausibility-analyst (judge whether indicator progress supports the outcome claims). Neither is needed for the pack to be usable.

Step 6 — Disclosure and scope boundary

  • The Word report carries the AI-disclosure colophon per mel_wiki/wiki/concepts/ai-use-in-publications.md. AI is never an author.
  • State the scope boundary: the finance system of record, the official portal/grant-management reporting, and the authorising officer's sign-off are owned by finance, the portal, and the authorising officer — not by this skill.

Output

Return the pack folder path and the manifest. Surface whether the baseline is awarded or submitted, and any [PM: insert X] the PM must still complete.

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