Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add konglong87/methodology-skills --skill goal-orientedgit clone --depth 1 https://github.com/konglong87/methodology-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/konglong87/methodology-skills/goal-oriented)<a href="https://agentmods.dev/skills/konglong87/methodology-skills/goal-oriented"><img src="https://agentmods.dev/badge/skills/konglong87/methodology-skills/goal-oriented/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/konglong87/methodology-skills/goal-oriented"><img src="https://agentmods.dev/badge/skills/konglong87/methodology-skills/goal-oriented.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.11440 |
| Opus 5 | $0.00012 | $0.05720 |
| Sonnet 5 | $0.00005 | $0.02288 |
| Haiku 4.5 | $0.00002 | $0.01144 |
Grade A, and why
goal-oriented scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 1,422 lines — stays where its author put it; the contents beside it link to each section on GitHub.
目标导向思维
前置协议
环境检测
# 检测当前项目信息
PROJECT_ROOT=$(git rev-parse --show-toplevel 2>/dev/null || echo "unknown")
BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
COMMIT=$(git rev-parse --short HEAD 2>/dev/null || echo "unknown")
echo "PROJECT: $PROJECT_ROOT"
echo "BRANCH: $BRANCH"
echo "COMMIT: $COMMIT"
# 检查是否在 Git 仓库中
if [ "$PROJECT_ROOT" = "unknown" ]; then
echo "WARNING: Not in a Git repository"
fi
前置技能检查
dependencies 检查(无依赖):
此技能无前置依赖,可直接执行。
工件目录初始化:
# 确保工件目录和目标目录存在
mkdir -p memory/artifacts/goal-oriented
mkdir -p memory/goals
用户意图确认
根据用户消息判断:
检查点:
- 用户请求是否包含任务特征(行动指令、多步骤需求)
- 是否需要创建新目标、更新现有目标或验证目标
- 确定是纯信息查询还是需要执行的任务
意图分类:
- 创建目标:用户提出新任务,当前无 pending 目标
- 调整目标:用户修改需求,当前有 pending 目标
- 验证目标:AI 认为完成,需要验证目标达成情况
- 查询/对话:纯信息查询或简单问答,无需创建目标
需求细化与方案探索(强制)(新增)
触发时机:创建目标文件后,执行任务前
强制动作:依次调用前置技能链
前置技能链:
1. prompt-enhancer(需求细化+方案探索)
触发条件:
- 用户需求模糊或不完整
- 复杂任务(涉及多个模块/系统)
- 需要探索多种方案
执行步骤:
创建目标后 → 调用 prompt-enhancer
↓
需求细化(每个关键点问3-4问题)
↓
方案探索(头脑风暴3-5种方案)
↓
用户选择方案
↓
生成需求方案工件
工件位置:memory/artifacts/prompt-enhancer/result-{timestamp}.json
价值:
- 避免理解偏差
- 充分论证方案
- 发现隐藏需求
2. planning(实施规划+plan-review)
触发时机:prompt-enhancer 完成后
强制动作:生成实施计划并经过用户确认
执行步骤:
读取需求方案工件 → planning
↓
步骤分解(MECE原则)
↓
依赖识别
↓
资源规划
↓
风险评估
↓
生成实施计划
↓
plan-review(用户确认)
↓
生成实施计划工件
工件位置:memory/artifacts/planning/result-{timestamp}.json
价值:
- 明确执行路径
- 识别依赖关系
- 提前评估风险
- 用户确认计划
经验检索(强制)
触发时机:planning 完成后
强制动作:调用 experience-manager 技能检索历史经验
执行步骤:
-
提取关键词
从用户原始需求中提取关键词: - 技术关键词:框架、库、工具名称 - 功能关键词:核心功能描述 - 问题关键词:错误类型、问题场景 -
写入请求工件
Write( file_path="memory/artifacts/goal-oriented/experience-request.json", content={ "requesting_skill": "goal-oriented", "action": "retrieve", "task_keywords": ["关键词1", "关键词2"], "task_type": "bugfix|feature|refactor", "technologies": ["Technology1", "Technology2"] } )
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 1,422 lines · 24 tokens per session scan A f1b17b70e334
goal-oriented is a skill published in the GitHub repository konglong87/methodology-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 11,440 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
importing-a-codebase
Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced project (brainstorming).
starting-a-new-project
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…
writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
brainstorming
Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small.
reviewing-changes
Use when a review package asks you to review a plan step's change set (todo.startReview): you are the REVIEWER, not the author. How to judge an agent-written diff, file findings with addreviewcomment, and settle with exactly one reviewverdict.