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 jszmajda/lid --skill linked-intent-devgit clone --depth 1 https://github.com/jszmajda/lidWrote 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/jszmajda/lid/linked-intent-dev)<a href="https://agentmods.dev/skills/jszmajda/lid/linked-intent-dev"><img src="https://agentmods.dev/badge/skills/jszmajda/lid/linked-intent-dev/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/jszmajda/lid/linked-intent-dev"><img src="https://agentmods.dev/badge/skills/jszmajda/lid/linked-intent-dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00087 | $0.07439 |
| Opus 5.5 | $0.00035 | $0.02976 |
| Sonnet 5.5 | $0.00017 | $0.01488 |
| Haiku 4.5 | $0.00009 | $0.00744 |
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 5d 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 — 265 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 it — the phase output in full, or an authorized inspector's summarized findings (see Specification and inspection instruments below) — incorporate numbered feedback, and proceed only on explicit approval. Each stop is mandatory; the stops are the mechanism realizing the HLD tenet Every phase is inspected. Skipping stops is the single most common way this workflow degrades into a rush. (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 — unless the user has expressly authorized a consolidated cadence: a warned override, or an opt-in experiment they have declared.)
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.
What ships with it
6 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.
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.
- 5d ago Changed · +53 lines ea2dde2d8b65
- 1mo ago First seen · 212 lines · 87 tokens per session scan A 1ec8b2f5e0e0
linked-intent-dev is a skill published in the GitHub repository jszmajda/lid (112 stars, last pushed 3d ago), licensed MIT. It adds 87 tokens to every session and 7,439 once invoked, about $0.0003 per session on Opus 5.5. 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.
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