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client judgment
Draft and review evidence-based client communications that preserve authority and prevent unauthorized commitments.
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client judgment
Example session with this skill installed
The client wants to know if the signup flow is ready for tomorrow's demo. The code has a TODO for the email verification step, and I haven't tested it on Safari yet. I plan to test Safari tonight.
- Read your context and instructions
- Compiled the client judgment
I have reviewed the state of the signup flow against the demo requirement. The missing email verification and lack of Safari testing are consequential blockers for a live demo.
Stakeholder Message Draft
Subject: Status of signup flow for tomorrow's demo
The signup flow is not yet ready for tomorrow's demo. While the primary logic is implemented, the email verification step is currently a placeholder and I have not yet verified the layout on Safari.
I am testing Safari tonight and will update you by 9:00 AM tomorrow on whether we can use a bypass for the demo or if we should defer that specific part of the walkthrough.
Next steps
- Complete Safari layout testing and document any rendering regressions.
- Determine if a manual database flag can bypass the missing email verification for demo purposes.
- Confirm the 9:00 AM check-in with the client to make the final "go/no-go" decision.
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About this skill
Managing client expectations during software delivery requires a delicate balance between technical accuracy and professional authority. This skill prevents the common pitfalls of over-promising, accidental admissions of liability, or burying a "yes" in technical jargon. It helps you draft and review communications regarding readiness, bugs, delays, and scope by grounding every response in verified evidence rather than optimistic assumptions.
What it does
- Drafts readiness updates by checking implementation facts against intended use cases to ensure honest status reporting.
- Reviews stakeholder replies to remove accidental commitments, invented dates, or unauthorized scope changes.
- Identifies delivery blockers and translates technical issues into clear business impacts for non-technical recipients.
- Preserves sender authority by maintaining professional boundaries and avoiding defensive or evasive language.
- Structures next steps by distinguishing between firm commitments, current facts, and proposed future actions.
How it works
- Evidence gathering: The agent inspects supplied facts or code state to distinguish between "local pass" and "client accepted."
- Decision matching: It selects a response pattern based on whether requirements passed, a blocker exists, or a limitation is present.
- Commitment audit: The agent strips out any manufactured dates or free work that the user has not explicitly authorized.
- Voice adaptation: It generates a concise draft under 100 words for chat or a structured report for formal email.
Frameworks & tools
This skill is framework-agnostic and works with any software project context. It integrates with code repositories to verify TODOs, environment states, and deployment logs before drafting.
Why this beats prompting it yourself
Generic LLM prompts often produce overly apologetic or corporate-sounding fluff that can lead to legal or commercial scope creep. This skill enforces strict grounding rules that separate what is actually "done" from what is merely "possible," protecting your time and professional reputation.
Use cases
- Missed deadlines: Explaining a delay due to third-party dependencies without taking undue blame.
- Readiness checks: Telling a founder if a prototype is stable enough for prospect interviews.
- Scope requests: Declining or deferring "quick fixes" that fall outside the current sprint or contract.
- Bug reports: Acknowledging a verified defect while providing a concrete timeline for the next status update.
Known limitations
This skill does not provide legal or HR advice. It cannot authorize project changes, deploy code, or sign commercial agreements. Drafts require user verification of missing facts.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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