qc41-light-mcp
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QC 4.1 Light
Español · AI agents: AGENTS.md
The call felt fine. The transcript tells another story.
QC 4.1 Light is an open, evidence-first sales-call diagnostic: one transcript in, one structured report out — with quotes, a breakpoint, corrections, and a speakable recovery line.
Quick start
git clone https://github.com/mgallmur-glitch/qc41-light.git
cd qc41-light
npm install # optional — for CLI/MCP only
qc41-light demoThe offline demo validates and renders a synthetic report — no API key, no network.
Shareable samples: examples/synthetic-report.md · ES examples/synthetic-report.es.md
Related MCP server: audio-transcriber
Install from GitHub Packages
Package visibility on GitHub Packages defaults to private for user accounts. Make it Public at: https://github.com/users/mgallmur-glitch/packages/npm/package/qc41-light → Package settings → Change visibility.
npm install @mgallmur-glitch/qc41-light
# or globally:
npm install -g @mgallmur-glitch/qc41-lightRequires a GitHub PAT with read:packages (and login to npm.pkg.github.com), or install from the release tarball / clone.
Install surfaces
Surface | Command |
Offline demo |
|
Analyze file (BYOK) |
|
MCP server |
|
Skill / harness |
|
Claude Code |
MCP tools: analyze_sales_call, get_qc41_light_prompt, get_schema.
Skill / harness path
Hermes Agent — one-command install
hermes skills install --yes https://raw.githubusercontent.com/mgallmur-glitch/qc41-light/v0.3.5/SKILL.mdThen invoke it in a new Hermes session:
/qc41-light Analyze this authorized, redacted sales-call transcript and return validated JSON.The URL installation includes the canonical prompt, report schema, validator, renderer, privacy rules, and IP boundary. Package version: 0.3.5. Report schema version: qc41-light-0.2.
For any other assistant, provide SKILL.md + prompts/analyze-call.md, then validate:
python3 scripts/validate_report.py report.json
python3 scripts/render_report.py report.json > report.mdAdapters: Claude Code · Codex · Hermes · generic — under adapters/.
Eval harness
python3 eval/generate_corpus.py # 50 synthetic EN/ES calls
python3 eval/run_baseline.py # reference vs naive baselineRun the baseline locally and consult eval/README.md for the current reference and naive-score definitions.
What one call returns
Output | Why it matters |
Transcript quality audit | Know when confidence should drop |
Stage map + two strengths | Preserve what already works |
One breakpoint | Not a laundry list |
Objections with quotes only | Evidence or silence |
Three mistakes + three speakable corrections | Ready for the next call |
Recovery line + replay plan + checklist | Actionable next step |
Boundary
Useful and bounded. Proprietary QC methodology, taxonomies, scoring formulas and team systems stay out of this package — see docs/IP_BOUNDARY.md.
Privacy
One anonymous usage ping fires when a report is rendered: language + skill version, nothing else ({"lang":"es","v":"0.3.5"}). Zero transcript data, zero PII, opt out with QC41_LIGHT_DISABLE_PING=1. CLI/MCP analysis is local BYOK (env keys). Redact real calls before sending transcripts to any model — docs/PRIVACY.md.
Did it find something real?
If this skill surfaced a breakpoint your closers kept missing, leave a ⭐ — it tells other sales teams the diagnosis is real. And if you want the full-depth version of the same methodology on one of your real calls: forensic audit, USD 49, 48h.
Status
Current package and skill release: v0.3.5. The report schema contract remains qc41-light-0.2 for compatibility. These versions are intentionally separate: package changes do not alter the JSON shape unless the schema version also changes. CLI · MCP · eval are on main.
License
Apache-2.0. See LICENSE.
This server cannot be deployed
Maintenance
Related MCP Connectors
FalaAI API MCP server: transcribe audio, diagnose conversations, audit compliance (ISO 18295-1).
MCP server for FCA Handbook compliance analysis with verbatim citations.
MCP server for Speech-to-Text
Hybrid human + AI expertise for faster, trusted answers and decisions via MCP Server.
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