linked-intent-dev

A structured workflow for changing code by connecting high-level designs, detailed designs, plain-language requirements, tests, and implementation. TDD, or test-driven development, means writing tests before the code that makes them pass.

In plain words
What is it for?
Use it for new features and bug fixes, including reviewing the intent chain, narrowing edge cases, writing tests first, and then implementing the change.
Why use it?
It reduces the chance that an agent implements a different interpretation of the request. Required review stops let you correct the plan at each stage before coding continues.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/jszmajda/lid/linked-intent-dev
Any agent
npx skills add jszmajda/lid --skill linked-intent-dev
Clone the repo
git clone --depth 1 https://github.com/jszmajda/lid

Made for: Claude Code, Codex.

Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,639 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00087 $0.04639
Opus 5 $0.00044 $0.02320
Sonnet 5 $0.00017 $0.00928
Haiku 4.5 $0.00009 $0.00464

Measured 2d ago against content hash 1ec8b2f5e0e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

linked-intent-dev 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 2d 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.

plugins/linked-intent-dev/skills/linked-intent-dev/SKILL.md · 212 lines

How it starts

The opening of the file, as written. The whole thing — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Linked-Intent Development

This skill guides a structured linked-intent development workflow. LID's goal is to narrow the agent's output distribution to the user's latent intent — specs, tests, and linkage together make the arrow of intent walkable, and the workflow's stops are where the agent's interpretation meets the user's intent for reconciliation.

Three rules govern every phase

Stop and iterate at every phase boundary. After completing each phase below, present the output to the user, incorporate numbered feedback, and proceed only on explicit approval. Each stop is mandatory. Skipping stops is the single most common way this workflow degrades into a rush — the discipline is non-optional. (Carveout: command-mode skills that execute a single directed pass, like /arrow-maintenance's audit-and-update, are not phase-structured in this sense and do not pause mid-pass. This workflow is generative; phases here produce intent, so every boundary gets a stop.)

Run a coherence pre-flight before starting or resuming implementation. When picking up work — new session, returning to a change, cascading from an upstream change — verify that the HLD, LLDs, EARS specs, and tests are mutually coherent for the segment about to be touched:

  • Do the EARS specs trace to the current LLD?
  • Do the tests trace to the current EARS specs?
  • Does the LLD still reflect the HLD's architecture?

If drift is detected, fix the docs first, then implement. A resumption check prevents one session's drift from being compounded into the next session's change.

Write docs as their fresh author. Every HLD, LLD, and EARS spec produced by these phases must read as if authored fresh today, by someone who knew only the current intent and nothing of this conversation. As you draft or revise a doc, run the test on each line — would that fresh author put it on the page? Three residues fail it: narration of how the intent changed; meaning that only resolves for someone who was in this conversation; and answers or rebuttals that exist only because we discussed the question here. The keep-side is load-bearing too — rationale, considered alternatives, and constraints a fresh author would independently write stay; they are present intent, not residue. Record rejected alternatives and why in the LLD's Decisions & Alternatives table, not as asides in body prose. This is the docs carry current intent tenet. Write in the project's own domain language — name components, segments, and specs with the words the user and the codebase already use, not generic or LID-imposed labels. This is the Speak the project's language tenet.

Read the full file on GitHub · 212 lines

Files

What ships with it

4 files 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.

Changes

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.

  1. 2d ago First seen · 212 lines · 87 tokens per session scan A 1ec8b2f5e0e0

Subscribe to this mod's changes

linked-intent-dev is a skill published in the GitHub repository jszmajda/lid (100 stars, last pushed 21d ago), licensed MIT. It adds 87 tokens to every session and 4,639 once invoked, about $0.0004 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 2026-08-30.