1on1-coach

Étoiles12

Forks1

Mis à jour30 avril 2026 à 20:14

Analyze a 1on1 meeting transcript and generate three output documents: a shareable summary for the team member, a private meeting analysis, and Socratic coaching questions for the manager. Use this skill whenever the user mentions a 1on1, one-on-one, manager meeting, team meeting transcript, or feedback session, or wants to process, summarize, or analyze any meeting between a manager and a team member — even if they do not use the word "transcript" or "1on1" explicitly. Also use it when the user provides a Fathom, Otter, or similar transcript file.

Installation

Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.

Source

abrahamvallez

abrahamvallez/skills

Ouvrir le dépôt GitHub Voir les dépôts du créateur

Téléchargement

Métiers associésSOC

Basé sur la classification professionnelle SOC

Responsables des ressources humainesProfessions de direction et de gestion·SOC 11-3121

Explorateur de fichiers

6 fichiers

SKILL.md

readonly

name	1on1-coach
description	Analyze a 1on1 meeting transcript and generate three output documents: a shareable summary for the team member, a private meeting analysis, and Socratic coaching questions for the manager. Use this skill whenever the user mentions a 1on1, one-on-one, manager meeting, team meeting transcript, or feedback session, or wants to process, summarize, or analyze any meeting between a manager and a team member — even if they do not use the word "transcript" or "1on1" explicitly. Also use it when the user provides a Fathom, Otter, or similar transcript file.
argument-hint	Path to transcript (e.g. transcripts/2026-04-28-carlos.txt). Optionally add: lang=es to force output language.

1on1 Meeting Analyzer

Analyzes a 1on1 transcript and produces three output files using portable prompts in ./references/.

When to Use

Processing a 1on1 meeting transcript
Generating a shareable summary for the team member
Creating private coaching material for the manager

Procedure

Step 1 — Read the transcript

Read the transcript file the user indicated. If no file was specified, ask for the path. Verify the file exists and has content. If it is empty or missing, inform the user and stop.

Step 2 — Extract metadata

From the transcript content, extract:

Meeting date: look for an explicit date in the text or filename. If not found, use today's date in YYYY-MM-DD format.
Team member name: the participant who is NOT the manager.
Manager name: the other participant (the one conducting the 1on1).
Base filename: {date}-{member-name-lowercase-no-spaces} (e.g. 2026-04-28-carlos)
Output language: if the user specified a language (e.g. lang=fr, "en español"), use that. Otherwise detect the transcript language automatically.
1on1 type: classify the meeting using the type taxonomy in base-rules.md. Examples: check-in, career, unblocking, feedback, conflict, onboarding, or mixed: [type1] + [type2].

Step 3 — Ensure output folders exist

Make sure these folders exist, create them if needed:

outputs/shareable/
outputs/coaching/

Step 4 — Generate the three outputs

For each output, load the corresponding reference prompt and apply it to the transcript:

Output file	Reference prompt	Audience
`outputs/shareable/{base-name}-summary.md`	prompt-summary.md	Team member (shareable)
`outputs/coaching/{base-name}-analysis.md`	prompt-analysis.md	Manager (private)
`outputs/coaching/{base-name}-coaching.md`	prompt-coaching.md	Manager (private)

Output file names always use English suffixes (-summary, -analysis, -coaching) regardless of the output language. Only the file content is translated.

Apply shared formatting and language rules from base-rules.md to all three outputs.

Pass to each prompt:

Full transcript content
Extracted metadata (date, team member name, manager name, base filename)
Resolved output language
Detected 1on1-type

Step 5 — Confirm results

Report to the user:

✅ Analysis complete for the meeting on {date} with {member-name}. [Language: {language}]

Generated files:

📄 SHAREABLE (send to the team member):
   outputs/shareable/{base-name}-summary.md

🔒 PRIVATE (Manager only):
   outputs/coaching/{base-name}-analysis.md
   outputs/coaching/{base-name}-coaching.md

Plus depuis ce dépôt

même dépôt

bokata-ac-analyst

abrahamvallez/skills

Generates Gherkin Acceptance Criteria (Given/When/Then scenarios) using Feature Mapping and Example Mapping methodologies. Includes integrated discovery phase that asks clarifying questions about business rules and edge cases before generating criteria. Use this skill whenever you need testable specs for User Tasks, need to define business rules as scenarios, or want to formalize acceptance criteria from a backbone, PRD, or raw user stories.

2026-07-1812

bokata-feature-mapper

abrahamvallez/skills

Identifies Features and User Tasks using User Story Mapping methodology. Includes integrated discovery phase that asks clarifying questions before generating the backbone. Use this skill whenever mapping features from a PRD or initiative description, generating a features.md, or decomposing user goals into tasks.

2026-07-1812

bokata-feature-slicer

abrahamvallez/skills

Slices a Feature into a Walking Skeleton and Increments Backlog — a ready-to-implement delivery plan. Internal phases (Steps and Incremental Options) are used as reasoning but not surfaced by default. Use this skill whenever you need to break down a Feature into implementable work — after generating a Features Backbone, when planning a sprint, or when a user asks to slice, decompose, or plan implementation of a feature.

2026-07-1812

bokata-research

abrahamvallez/skills

Unified Research Specialist — runs all three research phases (feature backbone, acceptance criteria, and slicer) before any downstream skill invocation. Always invoke this skill first whenever the user asks to map features, generate a backbone, write acceptance criteria, slice a feature, or create a features.md. Do not skip this skill even if the user provides a PRD or detailed context — research enriches every downstream output with domain vocabulary, actors, codebase patterns, and business constraints. Always produces Feature Research Summary, Criteria Research Summary, and Slicer Research Summary.

2026-03-0912

name	1on1-coach
description	Analyze a 1on1 meeting transcript and generate three output documents: a shareable summary for the team member, a private meeting analysis, and Socratic coaching questions for the manager. Use this skill whenever the user mentions a 1on1, one-on-one, manager meeting, team meeting transcript, or feedback session, or wants to process, summarize, or analyze any meeting between a manager and a team member — even if they do not use the word "transcript" or "1on1" explicitly. Also use it when the user provides a Fathom, Otter, or similar transcript file.
argument-hint	Path to transcript (e.g. transcripts/2026-04-28-carlos.txt). Optionally add: lang=es to force output language.

1on1 Meeting Analyzer

Analyzes a 1on1 transcript and produces three output files using portable prompts in ./references/.

When to Use

Processing a 1on1 meeting transcript
Generating a shareable summary for the team member
Creating private coaching material for the manager

Procedure

Step 1 — Read the transcript

Read the transcript file the user indicated. If no file was specified, ask for the path. Verify the file exists and has content. If it is empty or missing, inform the user and stop.

Step 2 — Extract metadata

From the transcript content, extract:

Meeting date: look for an explicit date in the text or filename. If not found, use today's date in YYYY-MM-DD format.
Team member name: the participant who is NOT the manager.
Manager name: the other participant (the one conducting the 1on1).
Base filename: {date}-{member-name-lowercase-no-spaces} (e.g. 2026-04-28-carlos)
Output language: if the user specified a language (e.g. lang=fr, "en español"), use that. Otherwise detect the transcript language automatically.
1on1 type: classify the meeting using the type taxonomy in base-rules.md. Examples: check-in, career, unblocking, feedback, conflict, onboarding, or mixed: [type1] + [type2].

Step 3 — Ensure output folders exist

Make sure these folders exist, create them if needed:

outputs/shareable/
outputs/coaching/

Step 4 — Generate the three outputs

For each output, load the corresponding reference prompt and apply it to the transcript:

Output file	Reference prompt	Audience
`outputs/shareable/{base-name}-summary.md`	prompt-summary.md	Team member (shareable)
`outputs/coaching/{base-name}-analysis.md`	prompt-analysis.md	Manager (private)
`outputs/coaching/{base-name}-coaching.md`	prompt-coaching.md	Manager (private)

Output file names always use English suffixes (-summary, -analysis, -coaching) regardless of the output language. Only the file content is translated.

Apply shared formatting and language rules from base-rules.md to all three outputs.

Pass to each prompt:

Full transcript content
Extracted metadata (date, team member name, manager name, base filename)
Resolved output language
Detected 1on1-type

Step 5 — Confirm results

Report to the user:

✅ Analysis complete for the meeting on {date} with {member-name}. [Language: {language}]

Generated files:

📄 SHAREABLE (send to the team member):
   outputs/shareable/{base-name}-summary.md

🔒 PRIVATE (Manager only):
   outputs/coaching/{base-name}-analysis.md
   outputs/coaching/{base-name}-coaching.md