Install
$ agentstack add skill-goodeye-labs-truesight-mcp-skills-truesight-workflows ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Truesight Workflows
Use this skill as the routing entrypoint across all Truesight MCP skills.
Role and scope
This skill is a router. It decides intent and routes to exactly one skill path.
Do not execute deep workflow steps here unless the user already asked for a very specific action and no further routing is needed.
Routing map
- Build custom live eval from scratch ->
create-evaluation - Evaluate one or more traces with an existing live eval ->
evaluate-trace - Analyze failure modes in dataset traces ->
error-analysis - Judge flagged items and add labeled outputs back to dataset ->
review-and-promote-traces - Start quickly from pre-built template ->
bootstrap-template-evaluation - Audit current eval setup and maturity ->
eval-audit - Build custom review web interface ->
build-review-interface - Generate synthetic test data for evaluation ->
generate-synthetic-data
Interactive Q&A protocol (mandatory)
BEFORE the first scoping question, search for a structured question tool (e.g., AskUserQuestion or similar interactive widget) and load it. Use that tool for EVERY scoping question. Fall back to plain-text lettered options ONLY if no such tool exists in the environment.
When user intent is unclear, ask one question at a time using the structured question tool (loaded per the HARD-GATE above). Structure each with a short header, options with labels and descriptions, and place the recommended option first. Do not add "(Recommended)" or similar annotations to option labels.
Question format:
Which workflow do you want to run first?
A) Evaluate traces with an existing live eval
B) Run error analysis on a dataset
C) Review and promote flagged traces
D) Bootstrap from a template
E) Create a new evaluation from scratch
F) Audit my eval setup
G) Build a custom review interface
H) Generate synthetic test data
Rules:
- Ask exactly one routing question per message.
- Use one follow-up question only if the answer is still ambiguous.
- After routing is clear, hand off immediately to the target skill.
Guardrails
- If user asks for
create-evaluation, do not decompose it into smaller skills. - Keep guidance scoped to currently available Truesight MCP tools.
- If user asks for functionality outside current MCP capabilities, state the gap clearly and offer the closest supported workflow.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: Goodeye-Labs
- Source: Goodeye-Labs/truesight-mcp-skills
- License: MIT
- Homepage: https://truesight.goodeyelabs.com/docs/mcp-integration
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.