How do I install the Mandate 2 1 5 Runtime Evidence Intake Guide skill?

Run npx skillmds@latest add jefflyt/mandate-2-1-5-runtime-evidence-intake-guide-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Mandate 2 1 5 Runtime Evidence Intake Guide safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Mandate 2 1 5 Runtime Evidence Intake Guide?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Mandate 2 1 5 Runtime Evidence Intake Guide free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Mandate 2 1 5 Runtime Evidence Intake Guide?

jefflyt (@jefflyt) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Mandate 2 1 5 Runtime Evidence Intake Guide by jefflyt

Name: Mandate 2 1 5 Runtime Evidence Intake Guide
Author: jefflyt

Mandate 2 1 5 Runtime Evidence Intake Guide

Gather natural-language context and generate runtime/process evidence collection guidance for Mandate 2.1.5 (Just-in-Time (JIT) and Identity-Based MCP Authentication), including concrete system command templates and artifact checklists for final compliance evaluation.

jefflyt Updated Sep 21, 2026

File contents

Mandate 2.1.5 Runtime Evidence Intake and Guidance Skill

Mandate

ID: 2.1.5
Title: Just-in-Time (JIT) and Identity-Based MCP Authentication

Mitigates

ASI03 Identity and Privilege Abuse
MCP05 Client Security Considerations
MCP06 Server Discovery and Verification

Purpose

Collect user-provided context in natural language, convert it into an evidence plan, and produce actionable steps and commands to generate runtime/process evidence for final assessment.

Step-by-Step Workflow

Elicit context in natural language. Ask for environment stack, deployment model, cloud/on-prem platform, logging/identity/security tooling, and data sensitivity profile.
Normalize context. Convert user responses into a structured environment profile: systems, owners, data stores, auth layers, monitoring tools.
Build mandate evidence matrix. Map required evidence types to concrete systems and responsible owners.
Generate evidence collection plan. Provide ordered steps to extract artifacts, expected output formats, and validation checks.
Generate system command pack. Produce commands with placeholders for the user environment and explain expected outputs.
Validate completeness. Mark each required artifact as collected, partial, or missing.
Produce final readiness report. Summarize what is sufficient for final pass/fail and what gaps remain.

Runtime/Process Evidence Required

Identity provider client configuration (grant type, PKCE, token TTL).
Token issuance/revocation logs with latency evidence.
Scope assignment policy and approval workflow.
Failed auth/access anomaly logs for MCP interactions.

Minimum User Inputs to Start

IdP application configuration export.
Token lifecycle metrics and revocation audit logs.
MCP access scope policy documents.

Command Templates (Adapt to User Environment)

OAuth/OIDC settings evidence (provider export): cat idp_client_config_.json
Token TTL/scope evidence logs: cat token_issuance_audit_.json
Revocation endpoint test (example): curl -X POST -d 'token='
MCP auth flow traces: rg -n "oauth|oidc|pkce|revocation|scope" .
Access anomaly logs: cat mcp_auth_anomalies_.log

Final Evaluation Logic

Pass only if code implements modern auth flow and runtime evidence confirms short-lived JIT scoped access with fast revocation.
Fail if either static analysis or IdP evidence indicates standing/broad access.

Output Contract

Return:

context_profile: normalized system context
evidence_requirements: checklist by artifact
command_plan: runnable command templates with placeholders
collection_status: per-artifact status
assessment_readiness: ready|not_ready
remaining_gaps: missing evidence blocking final verdict

Guardrails

Ask concise follow-up questions when context is ambiguous.
Keep commands read-only by default.
Call out commands requiring elevated privileges before execution.

---name: mandate-2-1-5-runtime-evidence-intake-guide-2description: Gather natural-language context and generate runtime/process evidence collection guidance for Mandate 2.1.5 (Just-in-Time (JIT) and Identity-Based MCP Authentication), including concrete system command templates and artifact checklists for final compliance evaluation.---# Mandate 2.1.5 Runtime Evidence Intake and Guidance Skill## Mandate- ID: 2.1.5- Title: Just-in-Time (JIT) and Identity-Based MCP Authentication## Mitigates- ASI03 Identity and Privilege Abuse- MCP05 Client Security Considerations- MCP06 Server Discovery and Verification## PurposeCollect user-provided context in natural language, convert it into an evidence plan, and produce actionable steps and commands to generate runtime/process evidence for final assessment.## Step-by-Step Workflow1. Elicit context in natural language. Ask for environment stack, deployment model, cloud/on-prem platform, logging/identity/security tooling, and data sensitivity profile.2. Normalize context. Convert user responses into a structured environment profile: systems, owners, data stores, auth layers, monitoring tools.3. Build mandate evidence matrix. Map required evidence types to concrete systems and responsible owners.4. Generate evidence collection plan. Provide ordered steps to extract artifacts, expected output formats, and validation checks.5. Generate system command pack. Produce commands with placeholders for the user environment and explain expected outputs.6. Validate completeness. Mark each required artifact as collected, partial, or missing.7. Produce final readiness report. Summarize what is sufficient for final pass/fail and what gaps remain.## Runtime/Process Evidence Required1. Identity provider client configuration (grant type, PKCE, token TTL).2. Token issuance/revocation logs with latency evidence.3. Scope assignment policy and approval workflow.4. Failed auth/access anomaly logs for MCP interactions.## Minimum User Inputs to Start- IdP application configuration export.- Token lifecycle metrics and revocation audit logs.- MCP access scope policy documents.## Command Templates (Adapt to User Environment)- OAuth/OIDC settings evidence (provider export): cat idp_client_config_<env>.json- Token TTL/scope evidence logs: cat token_issuance_audit_<date>.json- Revocation endpoint test (example): curl -X POST <revocation-endpoint> -d 'token=<token>'- MCP auth flow traces: rg -n "oauth|oidc|pkce|revocation|scope" .- Access anomaly logs: cat mcp_auth_anomalies_<date>.log## Final Evaluation Logic- Pass only if code implements modern auth flow and runtime evidence confirms short-lived JIT scoped access with fast revocation.- Fail if either static analysis or IdP evidence indicates standing/broad access.## Output ContractReturn:- context_profile: normalized system context- evidence_requirements: checklist by artifact- command_plan: runnable command templates with placeholders- collection_status: per-artifact status- assessment_readiness: ready|not_ready- remaining_gaps: missing evidence blocking final verdict## Guardrails- Ask concise follow-up questions when context is ambiguous.- Keep commands read-only by default.- Call out commands requiring elevated privileges before execution.

Frequently asked questions