smithery.ai

instruction-adherence

Use when instruction drift is likely: multi-step tasks, mid-task detours (tooling upgrades), or when agents must consult MCP memory / Skills / sessions and re-anchor repeatedly.

First seen Apr 2, 2026

Installation

$ npx skills add https://smithery.ai

Summary

  • Use when instruction drift is likely: multi-step tasks, mid-task detours (tooling upgrades), or when agents must consult MCP memory / Skills / sessions and re-anchor repeatedly.
  • Triggers: 'stay on track', 'follow instructions', 'resume main task', 'detour', 'intermediate task done'.

Similar popular skills

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npx skills add https://smithery.ai

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
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GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,204 B
  • docs SUMMARY.md 312 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Skill: Instruction Adherence (Stay On Track)

Scope

This Skill is about reliably following instructions across:

  • Multiple instruction sources (system/developer/mode files, repo docs, user request)
  • Memory sources (Skills registry, sessions, lessons/patterns)
  • Multi-step execution where detours happen (e.g., “improve CLI tooling” mid-stream)

Inputs

  • The current user request (objective + success criteria)
  • The active mode/persona (if any)
  • Repo guardrails (AGENTS.md, testing commands, server --check rule)

Procedure

1) Capture an “Instruction Snapshot” (mandatory)

In the active session’s WORKING_NOTES.md, write a short snapshot:

  • Objective: 1 sentence
  • Must do: 3–7 bullets
  • Must not: 3–7 bullets
  • Evidence: what output/tests/checks will prove done

This becomes the “north star” when you get interrupted.

2) Run the memory retrieval ritual (Skills → Sessions → Lessons)

  • Skills: open docs/agi/SKILLS.md and follow any matching SOP.
  • Sessions: find/continue a session on the same topic.
  • Lessons/Patterns: pull stable guidance from docs/agi/* as needed.

If MCP tools are available, prefer them; otherwise use:

  • node tools/dev/md-scan.js --dir docs/agi --search "<topic>" --json
  • node tools/dev/md-scan.js --dir docs/sessions --search "<topic>" --json

3) Build a “Task Ledger” with explicit parent/child tasks

Use managetodolist with a structure that prevents detours from becoming the main task:

  • Parent task: user’s objective
  • Child tasks: discovery → implement → validate → document
  • If a detour is required (e.g., CLI tooling improvement), make it a child task with:

- Entry criteria (why it’s needed) - Exit criteria (what “done” means) - Return step (the exact next step to resume)

4) The Re-anchor loop (run after every subtask)

After any meaningful milestone (or after 3–5 tool calls):

  • Re-read the Instruction Snapshot
  • Mark completed tasks
  • Confirm the next step is still on the parent objective
  • If you drifted, explicitly choose to:

- Resume parent objective, or - Create a follow-up and stop the detour

5) “Detour complete → resume” protocol

When an intermediate task (like CLI tooling improvement) is completed:

  1. Record a one-paragraph summary + evidence in the session notes.
  2. Add/update a Skill or Lesson if it will recur.
  3. Immediately take the “Return step” you wrote in the task ledger.

Validation (evidence checklist)

  • Session contains an Instruction Snapshot.
  • Task ledger clearly separates parent objective vs detours.
  • At least one re-anchor checkpoint recorded in WORKING_NOTES.md.
  • SESSION_SUMMARY.md includes an Instruction Reflection:

- What instructions helped? - What was missing/wrong? - What durable doc/agent update was made?