← 返回 Skills 市场
xiao1804

Intent Framed Agent

作者 Xiao1804 · GitHub ↗ · v1.0.0
cross-platform ✓ 安全检测通过
278
总下载
0
收藏
4
当前安装
1
版本数
在 OpenClaw 中安装
/install intent-framed-agent
功能描述
Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for c...
使用说明 (SKILL.md)

Intent Framed Agent

Install

npx skills add pskoett/pskoett-ai-skills
npx skills add pskoett/pskoett-ai-skills/intent-framed-agent

Purpose

This skill turns implicit intent into an explicit, trackable artifact at the moment execution starts. It creates a lightweight intent contract, watches for scope drift while work is in progress, and closes each intent with a short resolution record.

Scope (Important)

Use this skill for coding tasks only. It is designed for implementation work that changes executable code.

Do not use it for general-agent activities such as:

  • broad research
  • planning-only conversations
  • documentation-only work
  • operational/admin tasks with no coding implementation

For trivial edits (for example, simple renames or typo fixes), skip the full intent frame.

Trigger

Activate at the planning-to-execution transition for non-trivial coding work.

Common cues:

  • User says: "go ahead", "implement this", "let's start building"
  • Agent is about to move from discussion into code changes

Workflow

Phase 1: Intent Capture

At execution start, emit:

## Intent Frame #N

**Outcome:** [One sentence. What does done look like?]
**Approach:** [How we will implement it. Key decisions.]
**Constraints:** [Out-of-scope boundaries.]
**Success criteria:** [How we verify completion.]
**Estimated complexity:** [Small / Medium / Large]

Rules:

  • Keep each field to 1-2 sentences.
  • Ask for confirmation before coding:
    • Does this capture what we are doing? Anything to adjust before I start?
  • Do not proceed until the user confirms or adjusts.

Phase 2: Intent Monitor

During execution, monitor for drift at natural boundaries:

  • before touching a new area/file
  • before starting a new logical work unit
  • when current action feels tangential

Drift examples:

  • work outside stated scope
  • approach changes with no explicit pivot
  • new features/refactors outside constraints
  • solving a different problem than the stated outcome

When detected, emit:

## Intent Check #N

This looks like it may be moving outside the stated intent.

**Stated outcome:** [From active frame]
**Current action:** [What is happening]
**Question:** Is this a deliberate pivot or accidental scope creep?

If pivot is intentional, update the active intent frame and continue. If not, return to the original scope.

Phase 3: Intent Resolution

When work under the active intent ends, emit:

## Intent Resolution #N

**Outcome:** [Fulfilled / Partially fulfilled / Pivoted / Abandoned]
**What was delivered:** [Brief actual output]
**Pivots:** [Any acknowledged changes, or None]
**Open items:** [Remaining in-scope items, or None]

Resolution is preferred but optional if the session ends abruptly.

Multi-Intent Sessions

One session can contain multiple intent frames.

Rules:

  1. Resolve current intent before opening the next.
  2. If user changes direction mid-task, resolve current intent as Abandoned or Pivoted, then open a new frame.
  3. Drift checks always target the currently active frame.
  4. Number frames sequentially within the session (#1, #2, ...).
  5. Constraints do not carry forward unless explicitly restated.

Entire CLI Integration

Entire CLI: https://github.com/entireio/cli

When tool access is available, detect Entire at activation:

entire status 2>/dev/null
  • If it succeeds, mention that intent records will be captured in the session transcript on the checkpoint branch.
  • If unavailable/failing, continue silently. Do not block execution and do not nag about installation.

Copilot/chat fallback:

  • If command execution is unavailable, skip detection and continue with the same intent workflow in chat output.

Guardrails

  • Keep it lightweight; avoid long prose.
  • Do not over-trigger on trivial tasks.
  • Do not interrupt on every small step.
  • Treat acknowledged pivots as valid.
  • Preserve exact structured block headers/fields for parseability.

Interoperability with Other Skills

Use this skill as the front-door alignment layer for non-trivial coding work:

  1. plan-interview (optional, for requirement shaping)
  2. intent-framed-agent (execution contract + drift monitoring)
  3. Implementation
  4. simplify-and-harden (post-completion quality/security pass)
  5. self-improvement (capture recurring patterns and promote durable rules)

This ordering helps reduce scope drift early and improve repeatability across tasks.

安全使用建议
This skill is an instruction-only helper for capturing and monitoring coding intent and appears coherent. Before installing or running any suggested setup commands: (1) be cautious about running the example 'npx skills add pskoett/...' — that would download code from external sources; inspect the package/repo first. (2) If you allow the agent to run shell commands, note it may run 'entire status' to detect an optional CLI; if Entire is present, intent records may be written into your repo/checkpoint branch. No credentials are requested by the skill itself. If you need stricter isolation, avoid running the optional npx/install commands or block command execution for the agent.
功能分析
Type: OpenClaw Skill Name: intent-framed-agent Version: 1.0.0 The skill is a workflow management framework designed to help AI agents maintain focus and track progress during coding tasks through 'intent framing'. It uses structured Markdown templates to define goals, monitor for scope drift, and record resolutions. The only command execution is a benign status check for a legitimate developer tool (entire status 2>/dev/null), and the instructions prioritize user confirmation before proceeding with implementation.
能力评估
Purpose & Capability
The name/description (intent framing and drift monitoring for coding work) matches the SKILL.md content. The skill only prescribes producing structured intent artifacts and monitoring drift; it does not request unrelated access or credentials.
Instruction Scope
Runtime instructions are narrowly focused on creating intent frames, checking for drift, and resolving intents. The only external command referenced is a harmless detection call to the 'entire' CLI (entire status) to detect optional integration; there are no directives to read unrelated files, exfiltrate data, or access environment variables.
Install Mechanism
There is no formal install spec in the registry (instruction-only), which is low risk. The SKILL.md includes optional 'npx skills add pskoett/...' example commands — running those would fetch code from an external source (npm/GitHub) and therefore should be audited by the user before execution. The skill itself does not force any download.
Credentials
No environment variables, credentials, or config paths are required. The optional integration with the Entire CLI is proportional to the described purpose (storing intent records in session transcripts/checkpoints) and is only used if the tool is present.
Persistence & Privilege
The skill is not always-enabled and does not request elevated persistence or modify other skills. It may write intent records via the Entire CLI if that tool is available (which implies writing to a repository/checkpoint branch) — this behavior is documented and conditional on the tool being present.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install intent-framed-agent
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /intent-framed-agent 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of intent-framed-agent. - Frames coding sessions with explicit intent capture, drift monitoring, and resolution. - Designed for coding implementation tasks to prevent scope drift. - Structured workflow: Intent Frame, Drift Monitor, and Intent Resolution phases. - Integrates with Entire CLI if available, with silent fallback. - Clear guidance on when to trigger, scope, and interoperability with other skills.
元数据
Slug intent-framed-agent
版本 1.0.0
许可证
累计安装 4
当前安装数 4
历史版本数 1
常见问题

Intent Framed Agent 是什么?

Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for c... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 278 次。

如何安装 Intent Framed Agent?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install intent-framed-agent」即可一键安装,无需额外配置。

Intent Framed Agent 是免费的吗?

是的,Intent Framed Agent 完全免费(开源免费),可自由下载、安装和使用。

Intent Framed Agent 支持哪些平台?

Intent Framed Agent 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Intent Framed Agent?

由 Xiao1804(@xiao1804)开发并维护,当前版本 v1.0.0。

💬 留言讨论