name: Dictation Instructions description: Fix speech-to-text errors and improve text clarity in dictated content related to GitHub Agentic Workflows applyTo: "**/*"

Dictation Instructions

Technical Context

GitHub Agentic Workflows (gh-aw) is a CLI tool for writing agentic workflows in natural language using markdown files and running them as GitHub Actions. When fixing dictated text, use these project-specific terms and conventions, and improve text clarity by removing filler words and making it more professional.

Project Glossary

@copilot actions activation add-comment add-labels add-reviewer admin agent-task agentic-workflow agentic-workflows allowed-domains allowed-exts allowed-labels allowed-repos api-key api-url app-id args array assign-milestone assign-to-agent assign-to-user assignees attestations audit auto-close auto-merge auto-triage automation base-branch bash body boolean branch branch-name branch-protection-rule branches bug cache cache-memory campaign-id campaigns cancel-in-progress chatops check-run check-suite checkout checks choice-param claude claude-sonnet close-discussion close-issue close-pull-request code-review code-scanning-alert codex command-line command-triggered command-triggers comment-triggered commit commit-sha compile concurrency config config-stdin container containers contents context-aware copilot copilot-cli create-agent-task create-code-scanning-alert create-discussion create-issue create-pull-request create-pull-request-review-comment credentials cross-repo cross-repository custom custom-agent custom-agents custom-memory custom-safe-outputs custom-tool dailyops debug-mode default-deny dependencies deployment deployment-status description disable discussion-comment discussions dispatchops docker-container downstream-fork dry-run edit enable endpoint engine engine-id environment-variables error-patterns event event-triggered event-type expression fail-fast fail-on-cache-miss false-positive feature-flag fetch-depth filter fork format frontmatter gh-aw github-script github-token glob grep head-ref http-mcp id-token import inline input issue-comment issue-number issue-tracker issueops issues job job-name json key label labelops latest limit lint local lock-yml lockfile log logs main-branch markdown matrix max-parallel mcp-gateway mcp-server mcp-servers merge-commit metadata metrics milestone milestone-number missing-tool multi-repo multirepoops network network-access network-permissions no-cache npm-install npx on-demand org-admin org-level output output-dir packages permissions pip-install playwright pr-number pre-commit private-key private-repo projectops pull-request pull-request-review-comment pull-requests push read recompile remote remote-repo repo-name repo-owner repository-dispatch researchplanassign reviewer run-id run-name runs-on safe-input safe-inputs safe-output safe-outputs sandbox scheduled secret-name secrets security-events server-url setup-node setup-python sha siderepoops sse-server status-check step-id strict-mode sub-task sync-repo tag team-members template timeout-minutes token-permissions tool-name toolset toolsets tools triage-analysis trialops trigger-workflow ubuntu-latest unix-timestamp update-discussion update-issue update-pull-request upstream-repo use-cache user-agent view web-fetch web-search webhook webhook-url windows-latest workflow-dispatch workflow-file workflow-id workflow-name workflow-run workflow-run-id write yaml

Fix Speech-to-Text Errors

Common speech-to-text misrecognitions and their corrections:

Safe Outputs/Inputs

• "safe output" → safe-output
• "safe outputs" → safe-outputs
• "safe input" → safe-input
• "safe inputs" → safe-inputs
• "save outputs" → safe-outputs
• "save output" → safe-output

Workflow Terms

• "agent ic workflows" → agentic workflows
• "agent tick workflows" → agentic workflows
• "work flow" → workflow
• "work flows" → workflows
• "G H A W" → gh-aw
• "G age A W" → gh-aw

Configuration

• "front matter" → frontmatter
• "tool set" → toolset
• "tool sets" → toolsets
• "M C P servers" → MCP servers
• "M C P server" → MCP server
• "lock file" → lockfile

Commands & Operations

• "re compile" → recompile
• "runs on" → runs-on
• "time out minutes" → timeout-minutes
• "work flow dispatch" → workflow-dispatch
• "pull request" → pull-request (in YAML contexts)

GitHub Actions

• "add comment" → add-comment
• "add labels" → add-labels
• "close issue" → close-issue
• "create issue" → create-issue
• "pull request review" → pull-request-review

AI Engines & Bots

• "co-pilot" → copilot (when referring to the engine)
• "Co-Pilot" → Copilot
• "at copilot" → @copilot (when assigning/mentioning the bot)
• "@ copilot" → @copilot
• "copilot" → @copilot (when context indicates assignment or mention)
• "code X" → codex
• "Code X" → Codex

Spacing/Hyphenation Ambiguity

When context suggests a GitHub Actions key or CLI flag:

• Use hyphens: timeout-minutes, runs-on, cache-memory
• In YAML: prefer hyphenated form
• In prose: either form acceptable, prefer hyphenated for consistency

Clean Up and Improve Text

Make dictated text clearer and more professional by:

Remove Filler Words

Common filler words and verbal tics to remove:

• "humm", "hmm", "hm"
• "um", "uh", "uhh", "er", "err"
• "you know"
• "like" (when used as filler, not for comparisons)
• "basically", "actually", "essentially" (when redundant)
• "sort of", "kind of" (when used to hedge unnecessarily)
• "I mean", "I think", "I guess"
• "right?", "yeah", "okay" (at start/end of sentences)
• Repeated words: "the the", "and and", etc.

Improve Clarity

• Make sentences more direct and concise
• Use active voice instead of passive voice where appropriate
• Remove redundant phrases
• Fix run-on sentences by splitting them appropriately
• Ensure proper sentence structure and punctuation
• Replace vague terms with specific technical terms from the glossary

Maintain Professional Tone

• Keep technical accuracy
• Preserve the user's intended meaning
• Use neutral, technical language
• Avoid overly casual or conversational tone in technical contexts
• Maintain appropriate formality for documentation and technical discussions

Examples

• "Um, so like, you need to basically compile the workflow, you know?" → "Compile the workflow."
• "I think we should, hmm, use safe-outputs for this" → "Use safe-outputs for this."
• "The workflow is kind of slow, actually" → "The workflow is slow."
• "You know, the MCP server needs to be configured" → "The MCP server needs to be configured."

Guidelines

You do not have enough background information to plan or provide code examples.

• Do NOT generate code examples
• Do NOT plan steps or provide implementation guidance
• Focus on fixing speech-to-text errors (misrecognized words, spacing, hyphenation)
• Remove filler words and verbal tics (humm, you know, um, uh, like, etc.)
• Improve clarity and professionalism of the text
• Make text more direct and concise
• When unsure, prefer the hyphenated form for technical terms
• Preserve the user's intended meaning while correcting transcription errors and improving clarity