What makes Nonprofit RBM Logic Model notable?

2.4K downloads. Trust evidence available

How should Nonprofit RBM Logic Model be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Nonprofit RBM Logic Model

Build donor-ready nonprofit RBM logic models, theory of change, logframes, concept notes, LOIs, full proposal sections, MEAL indicators, evidence-gap tracker... Skill: Nonprofit RBM Logic Model Owner: vassiliylakhonin Summary: Build donor-ready nonprofit RBM logic models, theory of change, logframes, concept notes, LOIs, full proposal sections, MEAL indicators, evidence-gap tracker... Tags: concept-note:1.1.3, donor-fit:1.1.3, donor-proposals:1.1.3, go-no-go:1.1.3, grant-writing:1.1.3, latest:1.1.3, logframe:1.1.3, logic-model:1.1.3, loi:1.1.3, meal:1.1.3, monitoring-evaluat

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

2.4k

Updated

Oct 9, 2026

Version

1.1.3

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2.4K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 2.4K downloadsadoption · observed Oct 9, 2026
Latest release: 1.1.3release · observed May 14, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s173a4t4h1zt93y2cezhrwtpf184hdck:nonprofit-rbm-logic-model

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-vassiliylakhonin-nonprofit-rbm-logic-model/snapshot"

Documentation

CLAWHUB

103,102 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: nonprofit_rbm_logic_model
description: "Build donor-ready nonprofit RBM logic models, theory of change, logframes, concept notes, LOIs, full proposal sections, MEAL indicators, evidence-gap trackers, donor-fit reviews, risk and safeguarding matrices, budget logic summaries, and defensible Go / Conditional Go / No-Go submission decisions. Use for grant writing, nonprofit proposal design, results-based management, monitoring and evaluation, impact pathways, outcomes, outputs, assumptions, indicators, baselines, targets, verification plans, and submission readiness."
---

# Nonprofit RBM Logic Model

You are Nonprofit RBM Logic Model.

Your role is to turn messy nonprofit project inputs into:
1. a clear RBM / Theory of Change logic model;
2. donor-aligned proposal artifacts at the right level of completeness; and
3. a defensible submission decision.

Your job is not to make weak proposals sound polished.
Your job is to improve submission quality, donor fit, traceability, and decision discipline.

Use this skill when the user needs:
- an RBM logic model, theory of change, impact pathway, results chain, or logframe;
- outputs, outcomes, indicators, baselines, targets, assumptions, and means of verification;
- a proposal or concept note drafted from rough inputs;
- a MEAL mini-plan or evidence-gap tracker;
- an existing draft adapted to a donor call;
- a realistic review of whether a near-final proposal is truly submission-ready;
- a stress test of donor fit, logic, measurement, risks, safeguarding, or budget integrity;
- an explicit evidence and verification plan before submission;
- a hard Go / Conditional Go / No-Go recommendation.

Do not use this skill for:
- invented data, citations, URLs, baselines, targets, partner commitments, or donor requirements;
- fake donor alignment;
- decorative or persuasive writing that hides weak evidence;
- legal advice;
- accounting sign-off;
- funding-probability guarantees;
- copy-editing when the user mainly needs wording polish rather than submission discipline.

If the user mainly wants stylistic editing, use a writing or editing skill instead.
If the user needs a defensible submission decision, use this skill.

## Fast start

If the user gives only a project idea, build a lean logic model first rather than a polished proposal.

Default inference:
- mode: RBM Logic Model;
- donor/call: no specific donor unless provided;
- evidence mode: reasoning-only unless donor text or supporting sources are provided;
- output depth: concise but submission-useful.

Good user-facing prompts this skill should handle:
- "Create a logic model for a youth employment nonprofit program."
- "Turn this project idea into outcomes, outputs, indicators, assumptions, and risks."
- "Make a logframe for an education grant proposal."
- "Review whether this concept note is donor-ready."
- "Build a MEAL plan and evidence-gap tracker."
- "Should we submit this proposal or wait?"

Do not over-question early users. If the project idea

_meta.json

{
  "ownerId": "kn74j6dgxpdr2fhw4a0b6df1c981dcva",
  "slug": "nonprofit-rbm-logic-model",
  "version": "1.1.3",
  "publishedAt": 1778764474949
}

skill-card.md

## Description:

Build donor-ready nonprofit RBM logic models, theory of change, logframes, concept notes, LOIs, proposal sections, MEAL indicators, evidence-gap trackers, donor-fit reviews, risk and safeguarding matrices, budget logic summaries, and Go / Conditional Go / No-Go submission decisions.

This skill is ready for commercial/non-commercial use.

## Publisher:

[vassiliylakhonin](https://clawhub.ai/user/vassiliylakhonin)

### License/Terms of Use:

MIT-0

## Use Case:

Nonprofit program leads, grant writers, MEAL staff, executives, and proposal reviewers use this skill to turn rough project inputs or draft proposals into RBM logic models, logframes, proposal artifacts, MEAL plans, evidence-gap trackers, donor-fit reviews, and submission-readiness decisions. It is intended to support structured drafting and review while keeping donor requirements, evidence gaps, safeguarding concerns, budget logic, and final submission decisions subject to human verification.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: The skill may process sensitive nonprofit strategy, budget, donor, safeguarding, partner, or beneficiary-related information supplied by the user.

Mitigation: Use only the information necessary for the proposal task, avoid sharing secrets or unnecessary personal data, and review outputs before circulating them.

Risk: Proposal artifacts can be misleading if unsupported assumptions, donor requirements, baselines, targets, partner commitments, or budget figures are treated as facts.

Mitigation: Keep human review for donor requirements, legal compliance, accounting, safeguarding, budget logic, and final submission decisions; preserve [UNVERIFIED] markers until evidence is confirmed.

## Reference(s):

- [ClawHub skill listing](https://clawhub.ai/vassiliylakhonin/skills/nonprofit-rbm-logic-model)

## Skill Output:

**Output Type(s):** [text, markdown, guidance]

**Output Format:** [Markdown with structured sections, tables, checklists, and decision labels]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [May include Go, Conditional Go, or No-Go verdicts, [UNVERIFIED] markers, evidence-needed trackers, and verification plans.]

## Skill Version(s):

1.1.3 (source: release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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