Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add VincentChuWaiChow/vanguard-frontier-agentic --skill case-to-resolution-protocolgit clone --depth 1 https://github.com/VincentChuWaiChow/vanguard-frontier-agenticWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vincentchuwaichow/vanguard-frontier-agentic/case-to-resolution-protocol)<a href="https://agentmods.dev/skills/vincentchuwaichow/vanguard-frontier-agentic/case-to-resolution-protocol"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/case-to-resolution-protocol/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vincentchuwaichow/vanguard-frontier-agentic/case-to-resolution-protocol"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/case-to-resolution-protocol.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 103 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00115 | $0.01380 |
| Opus 5 | $0.00057 | $0.00690 |
| Sonnet 5 | $0.00023 | $0.00276 |
| Haiku 4.5 | $0.00012 | $0.00138 |
Grade A, and why
case-to-resolution-protocol scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Case to Resolution Protocol
Purpose
This skill defines how a customer service case moves from first contact through routing, active resolution, and closure — and how every resolved case feeds the knowledge base so future cases resolve faster. It exists to ensure SLA accountability, consistent routing logic, and structured knowledge reuse across Dynamics 365 Customer Service. It does not replace human judgment on complex resolutions; it structures the handoffs so nothing falls through.
When to use
- A new case must be triaged and routed to a queue, team, or specialist.
- An active case risks breaching its SLA and needs escalation.
- A case is resolved and a knowledge article should be created or updated.
- Post-resolution CSAT is due and results must feed continuous-improvement loops.
- Multiple channels (email, chat, voice, social) need a unified intake view.
When NOT to use
- The case is already resolved and closed — routing decisions are moot.
- The matter is a product defect escalation requiring engineering triage — use your engineering escalation runbook.
- Regulated health or financial-services data handling requires compliance counsel that supersedes this protocol.
- You need live Dynamics 365 configuration changes — escalate to the service owner; this protocol is recommendation-only.
Participating agents
d365-customer-service-contact-center-agent(primary — case intake, routing, SLA monitoring, resolution, knowledge capture)
Inputs required
- Case description and channel of origin (email, chat, voice, social, web form)
- Customer or employee identity (authenticated or pending authentication)
- Priority signal or SLA entitlement reference
- Existing case history for this customer (if available)
- Knowledge base search results (Dynamics 365 Customer Service or SharePoint)
Evidence required
- Unified routing configuration (queues, skills, capacity rules) is in place
- SLA definitions and entitlements are configured in Dynamics 365 Customer Service
- Knowledge base is seeded and publishing workflow is active
- CSAT survey mechanism (Dynamics 365 Customer Voice or equivalent) is configured
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 121 lines · 115 tokens per session scan A e978ee6b7229
case-to-resolution-protocol is a skill published in the GitHub repository VincentChuWaiChow/vanguard-frontier-agentic (22 stars, last pushed 3d ago), licensed Apache-2.0. It adds 115 tokens to every session and 1,380 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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