check-answer-consistency SKILL.md skillA
check-answer-consistency from contextjet-ai/awesome-llm-observability is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add contextjet-ai/awesome-llm-observability/check-answer-consistency@git:20260705.4a31848Pins git:20260705.4a31848 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- contextjet-ai/awesome-llm-observability
- Path
skills/check-answer-consistency/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260705.4a31848, committed Jul 5, 2026
- Size
- 2,708 bytes
- Repository stars
- 45
- License
- a license file GitHub does not identify
Use this to get a cheap, reference-free signal that an LLM answer might be made up, by sampling the same prompt a few times and measuring agreement. Trigger on "is this answer reliable", "flag low-confidence answers", "cheap hallucination check", "confidence score without a ground truth", "self-consistency check". Ships a runnable, tested scorer you can put inline or on sampled traffic.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Check answer consistency
A model that knows the answer repeats it across re-samples; a hallucinating model wanders. This skill ships a small consistency scorer that turns that idea into a number, with no reference answer required.
## Use the bundled script
[`scripts/self_consistency.py`](scripts/self_consistency.py) is pure Python, no install needed:
```python
from self_consistency import consistency_score, is_likely_hallucination
answers = [call_model(prompt, temperature=0.7) for _ in range(5)]
score = consistency_score(answers) # 1.0 = all agree, ~0 = all differ
if is_likely_hallucination(answers, threshold=0.5):
route_to_review()
```
Run it directly to see confident vs unsure examples: `python scripts/self_consistency.py`.
## How to apply it
1. **Sample with temperature > 0** (e.g. 5 samples). Consistency methods need diversity; a single deterministic answer tells you nothing.
2. **Score, then act:** flag/block/route-to-review when the score is below your threshold, or attach it to the trace as a reliability signal.
3. **Reserve it for high-stakes answers** if latency matters, sampling N times multiplies cost and latency by ~N.
…Read the whole file at its exact version.
How to install
mdr add contextjet-ai/awesome-llm-observability/check-answer-consistency@sha256:bc274b892c13d74bThe line at the top of this page pins the label git:20260705.4a31848, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_gowvh4fstwjmrtv6)
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Versions
The registry has recorded 1 version of this file, committed on Jul 5, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (2708 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
contextjet-ai/awesome-llm-observability · 45 stars · license a license file GitHub does not identify · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_gowvh4fstwjmrtv6 GET https://markdownregistry.com/api/v1/resolve?ref=contextjet-ai/awesome-llm-observability/check-answer-consistency GET https://markdownregistry.com/api/v1/blob/bc274b892c13d74b8ed60a1be68dd54f5d9d79a464ef706f7e520ea39aa27355
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.