Alterlab Grant Reporting logo

Alterlab Grant Reporting

Organization
NVlabs
alterlab-grant-reporting

Drafts post-award grant deliverables across funder formats — NIH RPPR (Annual/Interim/Final via eRA Commons), NSF annual/final project reports and the public Project Outcomes Report (Research.gov), and Horizon Europe / ERC periodic and final reports (technical Part A/B + financial statements on the EU Funding & Tenders Portal) — plus milestone and deliverable tracking, budget-vs-actual variance narratives, no-cost-extension and rebudgeting justifications, and effort/closeout reporting. Computes report due dates from the award period with scripts/report_deadlines.py. Use when the user needs a grant progress or final report, post-award reporting, an RPPR, a periodic report, a no-cost-extension request, milestone tracking, or a budget-variance narrative. For writing new proposals prefer alterlab-research-grants; for TÜBİTAK proposals prefer alterlab-tubitak-proposal. Part of the AlterLab Academic Skills suite.

Overview

PublisherNVlabs
RepositorySkill2Env
Skill namealterlab-grant-reporting
Stars
189
Forks
18
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NVlabs on GitHub. Read the source before you install it.

Installation

Install the Alterlab Grant Reporting AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/NVlabs/Skill2Env/tree/main/SkillHub/skills/alterlab-grant-reporting
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/NVlabs/Skill2Env.git /tmp/Skill2Env
mkdir -p .claude/skills
cp -r /tmp/Skill2Env/SkillHub/skills/alterlab-grant-reporting .claude/skills/alterlab-grant-reporting
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Alterlab Grant Reporting in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Alterlab Grant Reporting on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Alterlab Grant Reporting is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Grant Reporting — Post-Award Deliverables Across Funder Formats

Post-award is where money already won has to be kept: funders release the next tranche only when a compliant progress report lands on time, and they claw back or flag awards when reports slip or numbers don't reconcile. This skill drafts those deliverables — progress/annual reports, final reports, milestone and deliverable tracking, budget-vs-actual narratives, and no-cost-extension (NCE) and rebudgeting justifications — in the exact shape each major funder demands.

It is the post-award counterpart to the pre-award proposal skills: it never writes a new proposal or a fresh budget request. It reports against an award that already exists.

When to Use This Skill

Use this skill when the user needs to:

  • Draft an NIH RPPR (Research Performance Progress Report) — Annual, Interim, or Final — section by section.
  • Draft an NSF annual or final project report, or the public-audience Project Outcomes Report.
  • Draft a Horizon Europe / ERC periodic or final report — the technical narrative (Part B) and the structured-table / financial-statement framing.
  • Track milestones and deliverables against a workplan and write the status narrative.
  • Write a budget-vs-actual (variance) narrative explaining over/under-spend by category.
  • Justify a no-cost extension or a rebudgeting / virement request.
  • Work out when each report is due from the award start/end dates (scripts/report_deadlines.py).

Does NOT Trigger — route these elsewhere

The request is really about…Route to
Writing a new proposal / project description for NSF, NIH, DOE, DARPA, NSTC (pre-award)alterlab-research-grants
A TÜBİTAK proposal (1001, 1002, etc.) — Turkish funder, pre-awardalterlab-tubitak-proposal
Akademik Teşvik annual incentive-points application (ÜAK)alterlab-akademik-tesvik
A data management plan / KVKK-compliant DMP for the proposal stagealterlab-kvkk-dmp
A recommendation / reference letter for a student or colleaguealterlab-recommendation-letters
Program / department accreditation assessment & assurance-of-learning reportsalterlab-accreditation-aol
Verifying that the citations in the report actually existalterlab-citation-verifier

This skill assumes the award is already made. If the user is still competing for funding, stop and route to the pre-award skill above.

The funder formats (verified)

Each funder fixes the structure; do not invent sections. Deep per-funder detail — every section, what goes in it, and which sections apply to which report type — lives in references/funder_formats.md. The essentials:

NIH — RPPR (submitted in eRA Commons)

Three report types share one section skeleton (A–I):

§TitleNote
ACover Page
BAccomplishmentsgoals, what was done, results, dissemination
CProductspublications, datasets, software, IP
DParticipantspersonnel + effort; D.1 is the only Section D item required on Interim/Final
EImpactimpact on the field, other disciplines, society
FChangeschanges/problems; rebudgeting & scope changes surface here
GSpecial Reporting Requirements
HBudgetAnnual (non-SNAP) only — not on Interim/Final
IOutcomesrequired on Interim & Final, public-facing

Report types: Annual (next budget period), Interim (filed with a competing renewal — becomes the Final report if the renewal is not funded), Final (closeout). See the references file before drafting.

NSF — project reports (submitted in Research.gov)

  • Annual project report — that year's activities and broader impacts.
  • Final project report — refers only to the final funded year (it is not cumulative).
  • Project Outcomes Report (POR) — a public-audience summary of no more than 800 words, separate from the final report.

Horizon Europe / ERC — periodic & final reports (EU Funding & Tenders Portal)

  • A Technical Report in two parts: Part A (structured tables, generated by the Portal from the Continuous Reporting module) and Part B (the narrative, mirroring the application form and reporting differences/deviations).
  • A Financial Report: individual and consolidated Financial Statements (plus a Certificate on the Financial Statements where the threshold applies).
  • A Continuous Reporting module that stays open for the whole project and feeds Part A automatically.

Deadlines — compute them, don't guess

Reporting deadlines are deterministic functions of the award dates, and missing one can suspend payments. Use the helper instead of recalling rules from memory:

bash
uv run python skills/faculty-life/alterlab-grant-reporting/scripts/report_deadlines.py \
    --funder nih-snap --budget-period-start 2026-09-01 --project-end 2028-08-31

It encodes only the verified rules (sourced in references/funder_formats.md):

  • NIH SNAP Annual RPPR ≈ 45 days before the next budget period start; non-SNAP ≈ 60 days before; Final RPPR within 120 days of the period-of-performance end.
  • NSF annual report 90 days before the budget-period end; final report and Project Outcomes Report within 120 days after the award end date.
  • Horizon Europe / ERC periodic (and final) report within 60 days after each reporting period ends.

The script prints the computed due dates as a table or JSON; it does no network I/O and always tells the user to confirm against the funder's own notice of award, because programs can override these defaults.

How to draft a report

  1. Identify the funder and report type first — that fixes the template. If the user hasn't said, ask (NIH vs NSF vs EU; Annual vs Final).
  2. Pull the deadline with report_deadlines.py from the award dates and lead with it, so the user knows the time pressure.
  3. Gather the inputs the sections need: aims/objectives and milestones, what was accomplished this period, products (publications, data, software), personnel and effort, and the budget figures (planned vs actual).
  4. Draft section by section in the funder's own order and headings. Never merge or rename funder sections. For each accomplishment, tie it back to a stated aim or deliverable.
  5. Write the variance narrative for any budget category off plan: state the planned vs actual amount, the reason, and the corrective action or the rebudgeting/NCE request it motivates. Detail and templates: references/budget_variance.md.
  6. For an NCE or rebudgeting request, use the justification structure in references/nce_rebudget.md: unspent-funds status, the programmatic reason, the revised timeline, and the explicit confirmation that no new scope or new funds are requested.
  7. Flag, never fabricate. Where a number, a publication, or an outcome is missing, mark it [TODO: confirm] for the user — do not invent figures, dates, DOIs, or results. If citations are involved, hand the reference list to alterlab-citation-verifier.

Guardrails

  • No invented facts. Budget figures, effort percentages, milestone dates, publication details, and award numbers come only from the user's materials. Mark anything missing as a [TODO] placeholder.
  • The user submits, not the skill. This skill drafts text; the user files it through eRA Commons / Research.gov / the EU Funding & Tenders Portal. The skill has no portal access and claims none.
  • Confirm deadlines against the notice of award. The calculator encodes the general rules; specific programs and cooperative agreements can override them.
  • Reporting period boundaries matter. An NSF final report covers only the final funded year; an NIH Final RPPR adds Section I Outcomes. Don't carry the wrong scope across report types.

References

  • references/funder_formats.md — full NIH RPPR A–I section guide (with which sections apply to Annual/Interim/Final), NSF report types, and Horizon Europe / ERC report structure, each with its source.
  • references/budget_variance.md — budget-vs-actual narrative template, variance categories, and worked examples.
  • references/nce_rebudget.md — no-cost-extension and rebudgeting/virement justification structures and the questions each funder asks.
  • scripts/report_deadlines.py — stdlib-only report-deadline calculator.

Part of the AlterLab Academic Skills suite.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Alterlab Grant Reporting AI skill do?

Drafts post-award grant deliverables across funder formats — NIH RPPR (Annual/Interim/Final via eRA Commons), NSF annual/final project reports and the public Project Outcomes Report (Research.gov), and Horizon Europe / ERC periodic and final reports (technical Part A/B + financial statements on the EU Funding & Tenders Portal) — plus milestone and deliverable tracking, budget-vs-actual variance narratives, no-cost-extension and rebudgeting justifications, and effort/closeout reporting. Computes report due dates from the award period with scripts/report_deadlines.py. Use when the user needs...

Why use Alterlab Grant Reporting on TypingMind?

Because you install it once and use it with any model. Alterlab Grant Reporting is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Alterlab Grant Reporting in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NVlabs/Skill2Env/tree/main/SkillHub/skills/alterlab-grant-reporting. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Alterlab Grant Reporting?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Alterlab Grant Reporting?

As many as you like. As long as a model supports skills, you can use Alterlab Grant Reporting with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Alterlab Grant Reporting AI skill free?

Yes. It is published on GitHub by NVlabs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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