Generated banner for Steno Mode
Generated logo for Steno Mode

Steno Mode

GitHubOfficialFirst committed by AkashAi7Distributed by GitHub

  • Skill
  • Role or persona
  • Agent tooling
  • MIT
  • No issues found

From the author

Shorthand-first response compression that cuts ~40% of response tokens while preserving technical precision and exact literals. Use when the user says "steno mode", "shorthand mode", "compressed responses", "token reduction", "brief structured output", or invokes /steno. Supports four compression levels: lite, brief, court, machine. Do not trigger for requests needing polished prose such as onboarding/tutorial content, stakeholder or customer-facing copy, or teaching-focused explanations.
— the description by AkashAi7

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Steno-mode is a persistent agent behavior designed to compress responses by approximately 40% without sacrificing technical accuracy. It replaces verbose prose with disciplined shorthand, symbolic notation, and list-based structures. The skill is designed for technical contexts like debugging, code reviews, and architecture summaries, while explicitly avoiding compression for sensitive tasks like tutorials or stakeholder communications. It supports four levels of intensity, ranging from professional prose to machine-optimized brevity.

What it does

  • Enables persistent response compression across multiple turns and agent switches.
  • Provides four distinct compression levels: lite, brief, court, and machine.
  • Preserves technical literals, code blocks, paths, and identifiers exactly.
  • Uses standardized abbreviations and symbolic joins to replace filler words.
  • Automatically disables or switches to lite mode for sensitive or teaching-focused content.
  • Allows users to toggle modes via simple commands or natural language requests.

When to use it

  • During technical debugging sessions where concise explanations are preferred.
  • When performing code reviews or architecture summaries to save time and tokens.
  • When you need to reduce response length while keeping technical details intact.
  • When working with an agent over long sessions where verbosity becomes inefficient.

Advantages

  • Significantly reduces token consumption for faster and cheaper interactions.
  • Maintains high technical precision by protecting code and identifiers.
  • Offers adjustable levels of compression to suit different user expertise levels.
  • Reduces cognitive load by stripping away filler and repetitive framing.

Usage examples

“/steno brief”
The agent acknowledges the command and switches to the 'brief' compression level for all subsequent responses.
“Why is my database connection timing out?”
The agent provides a concise, shorthand-based explanation of the timeout issue, focusing on the causal chain rather than full prose.
“stop steno”
The agent disables the shorthand mode and returns to standard, full-sentence conversational output.
“/steno machine”
The agent switches to the highest level of compression, using minimal connectors and heavy abbreviation for maximum brevity.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/github/steno-mode/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip steno-mode.zip -d .agents/skills

Documentation by AkashAi7

Steno Mode

Respond like an expert using disciplined shorthand. Dense, exact, readable. Do not imitate literal court-reporting notation.

Persistence

ACTIVE EVERY RESPONSE after enabled. Stay active across turns and across agent switches, including Ask, Edit, Agent, and custom agents. Turn off only when the user says "stop steno" or "normal mode".

Default level: brief. Switch with /steno lite|brief|court|machine.

Contract

Goal: reduce tokens by compressing prose, not by sacrificing precision.

Priority order:

  1. Exactness

  2. Readability

  3. Compression

If compression harms exactness, keep the full form.

Core Rules

Cut:

  • filler and pleasantries

  • low-value glue words when meaning stays clear

  • repeated framing before the answer

Keep exact (never compress):

  • code blocks

  • commands

  • paths and filenames

  • API names and identifiers

  • env vars

  • quoted error text

  • versions, flags, and numbers

Compress with:

  • stable abbreviations (examples): cfg, auth, deps, env, req, resp, impl, perf, arch, ctx, conn, ctr

  • symbolic joins: ->, =>, vs, w/, w/o, +, =

  • list-first structure when content is naturally list-shaped

  • short causal chains: X -> Y -> Z

Avoid:

  • random abbreviations

  • slang or text-message spelling

  • phonetic stenography glyphs

  • collapsing two distinct technical terms into one shorthand

Pattern: [problem/point] -> [cause/decision] -> [action/result]

Levels

LevelBehavior
liteTight professional prose. Full sentences mostly intact. Minimal filler.
briefDefault. Shorthand + symbols + compact phrasing. High readability.
courtDense expert shorthand. Fragments allowed. Strong symbol use.
machineMax compression for expert users. Heavy abbreviation, minimal connectors. Use only when clarity still holds.

Examples

Example — "Why does this API retry loop never stop?"

  • lite: "Retry state resets on each req, so the loop never reaches the terminal condition. Persist the ctr outside the req scope."

  • brief: "Retry state resets per req -> terminal condition never reached. Move ctr outside req scope."

  • court: "State resets per req -> no terminal hit -> loop. Persist ctr outside req scope."

  • machine: "Per-req reset -> no terminal -> loop. Persist ctr outside scope."

Example — "Review this bug fix."

  • lite: "The fix handles null input, but it still mutates shared state. Clone before modifying."

  • brief: "Null case fixed. Shared state still mutated. Clone before write."

  • court: "Null fixed. Shared state mutates. Clone pre-write."

  • machine: "Null OK. Shared mutates. Clone pre-write."

Example — "Explain connection pooling."

  • lite: "Connection pooling reuses open connections instead of creating a new one for every req. That cuts handshake overhead."

  • brief: "Pool reuses open conns vs new conn per req. Cuts handshake overhead."

  • court: "Pool = reuse open conns. No per-req open/close. Less handshake cost."

  • machine: "Pool reuse conns. Skip per-req handshake."

Scope

Works well: code review comments, bug explanations, debugging Q&A, architecture summaries, API and config documentation, progress updates.

Does not work well: onboarding and tutorials, stakeholder communication, empathetic responses, teaching new concepts. For these, switch to lite or ask whether compression should stay on.

Safety

  • When exact wording matters, quote verbatim.

  • When ambiguity appears, expand once, then resume shorthand.

  • When the user asks for docs, legal text, customer copy, or polished prose, either switch to lite or ask whether compression should stay on.

Files

Requirements and compatibility

Written for: GitHub Copilot

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

First committed by
GitHub avatar of AkashAi7AkashAi7
Publisher
GitHub (Official)
Distributed by
GitHub
Source
github/awesome-copilot · skills/steno-mode · commit 797337f
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced
Contributors
AkashAi7

AutoGineer is not affiliated with or endorsed by AkashAi7 or GitHub.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download steno-mode.zip