ai-for-management-consulting
Reusable Windsurf rules and Cursor agent skill files for cross-project AI-assisted development
Install / Use
npx skills add Ryukijano/agent-skills --skill ai-for-management-consultingInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Tags
Our assessment of ai-for-management-consulting
ai-for-management-consulting scores 53/100 on our quality scale, 2771st of 2,892 Automation skills we index.
Its SKILL.md is 2.1 KB long, well organised into 10 sections with 1 code example: moderately detailed.
It has no GitHub stars yet, so there is no community track record; judge it on its content.
Maintenance, license and trust
- We could not determine when the repository was last updated.
- Our last check on 2026-09-10 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 68/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-10-01. Automated pattern scan on 2026-10-01. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
ai-for-management-consulting compared with similar skills
All 4 of these similar skills score higher than ai-for-management-consulting; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| ai-for-management-consulting (this skill)by Ryukijano | 53 | 0 | — | SKILL.md |
| Agent-Reachby Panniantong | 100 | 101.3k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 89.3k | 1d ago | MCP Server |
| rufloby ruvnet | 100 | 78.8k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 31d ago | SKILL.md |
Frequently asked questions
- How do I install ai-for-management-consulting?
- Run
npx skills add Ryukijano/agent-skills --skill ai-for-management-consulting. The install tabs above show the steps for each supported agent. - Which AI agents does ai-for-management-consulting work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is ai-for-management-consulting safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 68/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is ai-for-management-consulting still maintained?
- We could not determine when the repository was last updated.
Skill content
View source on GitHubAI for Management Consulting
Description
Use AI to build AI-augmented consulting workflows for market analysis, synthesis of client data, hypothesis generation, or executive-ready deliverables.
When to use
You are building AI-augmented consulting workflows for market analysis, synthesis of client data, hypothesis generation, or executive-ready deliverables.
Usage
- Map tasks to GenAI fit (automate, augment, or avoid).
- Synthesize client documents and prior proposals.
- Draft proposals, status reports, and deliverables.
- Ground claims to sources and cite evidence.
Steps
- Map tasks to GenAI fit (automate, augment, or avoid).
- Synthesize client documents and prior proposals.
- Draft proposals, status reports, and deliverables.
- Ground claims to sources and cite evidence.
- Audit for hallucinations and epistemic risk.
- Deploy in client engagements, capture requirements from discovery calls, and measure time-to-insight and decision quality (Task-GenAI Fit-style).
Code pattern
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
# Cluster similar client documents or interview transcripts
vec = TfidfVectorizer(stop_words="english", ngram_range=(1, 2))
X = vec.fit_transform(documents)
sim = cosine_similarity(X)
Tuning notes
- Keep human consultants in the loop for ambiguous, high-stakes judgments.
- Trace every AI-generated claim to a source document or dataset.
- Calibrate outputs to client style, confidentiality, and ethical standards.
- Monitor for hallucinations and over-reliance on generic benchmarks.
Verification
- Build a document-synthesis pipeline and compare output to a manually written summary.
- Run a market-sizing model and verify inputs against published data.
- Audit a sample of GenAI outputs for factual accuracy and source attribution.
References
- https://doi.org/10.1007/s12599-026-00992-4
- https://www.wi.uni-muenster.de/research/publications/193019598
- https://doi.org/10.1016/j.infoandorg.2025.100559
- https://arxiv.org/abs/2409.06643
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.