discovery-rubric-auditor

discovery-rubric-auditor is a skill for Codex from nthnclrk/enablement-skills. It costs 90 tokens per session (945 once invoked), scanned A, original, MIT.

A review framework for comparing discovery calls, which are early sales conversations used to understand a buyer’s needs. It looks for repeated gaps across a comparable set of calls.

In plain words
What is it for?
Use it to audit calls with one rubric, measure recurring discovery weaknesses, establish a team baseline, and choose coaching priorities.
Why use it?
It prevents managers from treating one unusual call as proof of a team-wide problem.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to audit calls with one rubric, measure recurring discovery weaknesses, establish a team baseline, and choose coaching priorities.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nthnclrk/enablement-skills/discovery-rubric-auditor
Install

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.

Any agent
npx skills add nthnclrk/enablement-skills --skill discovery-rubric-auditor
Clone the repo
git clone --depth 1 https://github.com/nthnclrk/enablement-skills

Made for: Codex.

Wrote 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.

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README.md
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Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 945 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00090 $0.00945
Opus 5.5 $0.00036 $0.00378
Sonnet 5.5 $0.00018 $0.00189
Haiku 4.5 $0.00009 $0.00094

Measured 24d ago against content hash 60d23c352ab7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

discovery-rubric-auditor 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 24d 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.

skills/discovery-rubric-auditor/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Discovery rubric auditor

Compare discovery calls using a consistent rubric, then identify recurring behaviours that warrant coaching.

An audit needs a comparable sample, one rubric, and a few recurring gaps. One recorded call is call-review-coach. A pass/fail readiness decision is certification-program-builder.

Pattern. "In 7 of 9 mid-market first calls, reps named a problem and never asked what it costs. Coach the cost question next week. Do not rank the AE with two calls."

One-off. "The team needs better discovery. AE3 scored 2.1. Roll out a discovery refresh."

If you cannot say how often the gap appeared, in which comparable slice, it is not a pattern.

Inputs

Ask only for the inputs that change the audit:

  1. The sample and why these calls. One call: route to call-review-coach
  2. Comparison units: role, segment, stage, call type, time window
  3. Source coverage: recordings, transcripts, notes, or summaries
  4. Rubric source, or use the reference
  5. Reviewer count and whether they already calibrated
  6. The decision this audit must support: coaching priority or baseline, not certification

Continue from a thin sample with the limits named. Do not invent a leaderboard.

Supporting material

Read references/discovery-rubric-framework.md for anchors, calibration, and when a number is only directional. Skip it if the user already supplied a calibrated rubric and only wants the pattern read.

Procedure

  1. Frame the sample. Separate unlike roles, segments, stages, or call types. Done when each reported unit is comparable.
  2. Calibrate, or label the single-reviewer path. Agree anchors on benchmark calls first. One reviewer: delayed blind rescore and inter-rater reliability: not established. Done when disagreements greater than one point are resolved or named.
  3. Score with evidence. Every dimension gets a score or N/O, coverage, and confidence. Silence in missing audio is not a 1. Done when call-level evidence can be inspected.
  4. Check drift. Double-score a subset, or blindly rescore after a delay. Pause aggregation if anchors still disagree.
  5. Aggregate only comparable units. Count, median, distribution, N/O rate, coverage. Every number keeps its denominator. Fewer than three comparable calls per unit is directional.
  6. Separate pattern from one-off. Recurring clusters only. Frequency is not causation. Skill gap, process gap, and sample-shape issue are different findings.
  7. Pick a few interventions. Choose a response for each supported pattern: coaching, practice, process repair, or further investigation. For coaching, specify the behaviour to rehearse and the comparable future sample that could show improvement.

Read the full file on GitHub · 79 lines

Files

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.

Changes

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.

  1. 24d ago Changed 60d23c352ab7
  2. 2mo ago First seen · 79 lines · 90 tokens per session scan A 22b0a3c34af7

Subscribe to this mod's changes

discovery-rubric-auditor is a skill published in the GitHub repository nthnclrk/enablement-skills (16 stars, last pushed 25d ago), licensed MIT. It adds 90 tokens to every session and 945 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-30.

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