Skills when-analyzing-user-intent-use-intent-analyzer
📦
when-analyzing-user-intent-use-intent-analyzer
v1.0.0 Content revision r1 High Risk 📁 Filesystem access⚙️ External commands🔑 Env variables
Clarify User Intent Before Execution
Ambiguous requests can lead to incorrect plans, wasted work, and missed constraints. This skill analyzes intent, asks focused questions, and produces a clear execution brief.
Supports: Claude Codex Code(CC)
Stop for confirmation before installing.
Review the plan and obtain explicit user consent before changing files.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "when-analyzing-user-intent-use-intent-analyzer" from https://skillstore.io/skills/dnyoussef-when-analyzing-user-intent-use-intent-analyzer.md and its manifest at https://skillstore.io/api/skills/dnyoussef-when-analyzing-user-intent-use-intent-analyzer/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "when-analyzing-user-intent-use-intent-analyzer". Create an API with security.
Expected outcome:
- Likely intent: build a REST API with authentication and authorization.
- Clarifying question: which authentication method should be used?
- Next step: confirm scope before implementation begins.
Using "when-analyzing-user-intent-use-intent-analyzer". Make the app faster and cleaner.
Expected outcome:
- Likely intent: improve performance and simplify visible interface issues.
- Ambiguity: faster could mean load time, runtime response, or build speed.
- Next step: ask which performance metric matters most.
Using "when-analyzing-user-intent-use-intent-analyzer". Set up deployment for this project.
Expected outcome:
- Likely intent: create a repeatable production deployment workflow.
- Key assumptions: hosting target, secrets handling, and rollback process are undecided.
- Next step: confirm platform and release requirements.
Security Audit
High Riskv8 • 7/6/2026 Open versioned report
The audit confirmed real risks around full environment capture, mutable npx-based external tooling, shell script examples, and predictable /tmp output paths. Most static backtick findings were false positives caused by markdown fences or JavaScript template literals, and no prompt injection text was found.
4
Files scanned
1,270
Lines analyzed
11
Review items
0
False positives ignored
Confirmed security concerns (3)
High
Environment file access
environment: process.env,
The same process.env capture is later stored in memory as part of raw intent input. Persisting full environment data creates a clear secret disclosure risk.
High
Overbroad Environment and Project Context Capture
The workflow instructs agents to collect process.env, current working directory, filesystem clues, and recent edits for intent analysis. This can collect secrets and sensitive project metadata beyond what intent clarification requires.
The documented userInput and contextClues objects explicitly include process.env, cwd, filesystem analysis, recent edits, and memory storage. This confirms broad data collection, not just a naming false positive.
High
Mutable External Tool Execution
The skill declares claude-flow@alpha and repeatedly instructs npx execution. A mutable alpha dependency can change without review and execute third-party code during a clarification workflow.
The dependency and quick start examples explicitly name claude-flow@alpha and npx commands. The supply-chain risk is clear even though many backtick pattern matches were markdown fences.
Capability review items (11)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
High
Environment variable object
environment: process.env,
The skill captures the entire process.env object as context for intent analysis. Environment variables commonly contain tokens, keys, and service credentials.
Medium
Temp directory access
--output "/tmp/intent-brief.json"
The quick start writes an intent brief to a predictable /tmp path. This is a real data exposure and overwrite risk in shared environments, although it is documented as an example output.
Medium
Shell command substitution
USER_REQUEST=$(cat "$INPUT_FILE")
The script reads an arbitrary input file through command substitution and later passes that content to npx claude-flow. This can expose local file contents to external tooling if the script is used as written.
Medium
Shell command substitution
QUESTIONS=$(npx claude-flow@alpha agent-spawn \
The script captures output from an npx claude-flow agent-spawn command and builds the task from file contents. This is real external command execution with user-controlled analysis data.
Medium
Unix shell invocation
#!/bin/bash
This is a runnable shell script template, and the same block invokes npx claude-flow with file-derived input. The risk is external command execution in a workflow users may copy directly.
Medium
Unix shell invocation
#!/bin/bash
This shell script template invokes npx claude-flow, reads user responses, and writes local files. It is real executable workflow guidance, not just inert prose.
Medium
Node.js fs operations
await fs.writeFile(
The documented JavaScript writes the execution brief to disk using fs.writeFile. This is legitimate output behavior, but it can persist sensitive intent details without user path control.
Medium
Temp directory access
'/tmp/intent-analysis-result.json',
The execution brief is written to a fixed /tmp file path. Predictable temporary paths can leak sensitive task context or collide with other local files.
Medium
Temp directory access
--output "/tmp/intent-analysis-result.json"
The workflow exports final results to a fixed /tmp path. The output can contain interpreted user intent and execution details, so predictable temp storage is a real risk.
Medium
Temp directory access
--output "/tmp/intent-brief.json"
The integration example writes an intent brief to /tmp. Even as documentation, this directs users toward predictable temporary storage for potentially sensitive planning data.
Medium
Temp directory access
--context "/tmp/intent-brief.json"
The SPARC example reads the /tmp intent brief as workflow context. Reusing a predictable temporary path can expose or mix sensitive context between runs.
Risk Factors
📁 Filesystem access (7)
⚙️ External commands (86)
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🔑 Env variables (1)
Audited by: codex View Audit History →
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APA citation
DNYoussef. (2026). when-analyzing-user-intent-use-intent-analyzer security audit report (audit version 8) [Author version 1.0.0]. Skillstore. https://skillstore.io/skills/dnyoussef-when-analyzing-user-intent-use-intent-analyzer/audits/8BibTeX citation
@techreport{dnyoussef-dnyoussef-when-analyzing-user-intent-use-intent-analyzer-2026,
author = {DNYoussef},
title = {when-analyzing-user-intent-use-intent-analyzer security audit report (audit version 8)},
institution = {Skillstore},
year = {2026},
number = {8},
url = {https://skillstore.io/skills/dnyoussef-when-analyzing-user-intent-use-intent-analyzer/audits/8},
note = {Author version 1.0.0}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "when-analyzing-user-intent-use-intent-analyzer security audit report (audit version 8)"
version: "1.0.0"
type: report
authors:
- name: "DNYoussef"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/dnyoussef-when-analyzing-user-intent-use-intent-analyzer/audits/8"
identifiers:
- type: other
value: "skillstore:dnyoussef-when-analyzing-user-intent-use-intent-analyzer:audit:8"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: Medium 55
Architecture
100
Maintainability
87
Content
71
Community
83
Spec Compliance
What You Can Build
Clarify Vague Feature Requests
Turn a short or unclear feature request into scoped work with assumptions and next steps.
Prepare Stakeholder Briefs
Convert rough stakeholder input into a clear execution brief before planning begins.
Reduce Operational Ambiguity
Ask focused questions before acting on unclear support, DevOps, or workflow requests.
Try These Prompts
Clarify a Simple Request
Analyze this request for intent. Identify the likely goal, missing details, and one clarifying question: [paste request].
Rank Possible Interpretations
List three possible interpretations of this request. Rank them by likelihood and explain the evidence for each one: [paste request].
Create an Execution Brief
Create an execution brief from this request. Include interpreted intent, assumptions, constraints, risks, and confirmation questions: [paste request].
Analyze a High-Stakes Request
Perform a careful intent analysis for this high-stakes request. Limit context to nonsecret data, rank interpretations, and require confirmation before action: [paste request].
Best Practices
- Use this skill for ambiguous, complex, or high-impact requests.
- Limit context collection and redact secrets before analysis starts.
- Confirm the final interpretation before handing work to another workflow.
Avoid
- Do not run command examples without reviewing dependencies and file paths.
- Do not treat a probability score as user consent.
- Do not ask more clarifying questions than the decision requires.
Frequently Asked Questions
When should I use this skill?
Use it when a request is vague, multi-part, high-impact, or open to several interpretations.
Does it replace user confirmation?
No. It helps form a likely interpretation, but the user should confirm uncertain decisions.
Can it create an action plan?
Yes. It can produce a concise execution brief with scope, assumptions, risks, and next steps.
Does it need access to environment variables?
No. Environment capture should be disabled or redacted unless a user explicitly approves it.
Can I use it with Claude, Codex, and Claude Code?
Yes. The skill content is written for Claude, Codex, and Claude Code style workflows.
What are the main safety concerns?
Review external command examples, avoid full environment capture, and store outputs in approved paths.
Developer Details
Author
DNYoussefLicense
MIT
Author version
v1.0.0
Skillstore revision
r1
Ref
72d5025b022c77f7a51bdf5c1637c689c80e89d1
Maintenance freshness
7/18/2026
Usage
5 downloads · 271 views
File structure