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 ijust/intent-planner --skill intent-from-codegit clone --depth 1 https://github.com/ijust/intent-plannerWrote 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/ijust/intent-planner/intent-from-code)<a href="https://agentmods.dev/skills/ijust/intent-planner/intent-from-code"><img src="https://agentmods.dev/badge/skills/ijust/intent-planner/intent-from-code/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/ijust/intent-planner/intent-from-code"><img src="https://agentmods.dev/badge/skills/ijust/intent-planner/intent-from-code.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 | $0.00064 | $0.03633 |
| Opus 5.5 | $0.00026 | $0.01453 |
| Sonnet 5.5 | $0.00013 | $0.00727 |
| Haiku 4.5 | $0.00006 | $0.00363 |
Grade A, and why
intent-from-code 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 2mo 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
intent-from-code Skill
Core Mission
- Success Criteria (success if achieved; the scope-fixing / extraction / sensitive-info protection / recap procedure detail is consolidated into Execution Steps and the four rules, and only the outcomes are declared here):
- Reads the user-specified scope of existing code read-only and extracts intent candidates (roughly L0–L3), invariant candidates, and gaps of silence (places the code demonstrates but where no description of intent exists), writing them all out to
.intent/code-ingest/code-ingest.mdwith an inferred marker and a recovery basis (Step 1–3. R1.1) - Writes by full replacement only after all extraction is complete, so the same input yields the same output on re-run, without mixing old extractions with new ones (Step 3. R1.2)
- Governs the reading scope: requires the scope to be specified, and even when it is unspecified does not fall back to scanning the whole repository but proposes a recommended scope and asks for confirmation, never using anything outside the fixed scope as extraction input (delegated to read-scope. R2.1 / R2.4)
- When the scope is empty or does not exist, does not stop but states explicitly that "there is no readable material," and ends with an empty candidate list without filling in by guessing (fail-open. R2.3)
- At the end of the output, guides that "the user promotes approved items by copying them by hand into the discover / compass dialogue," and holds no machine handoff that auto-launches discover / compass from the skill (delegated to recap-and-promotion. R1.4 / R4.4)
- Limits writes to under
.intent/code-ingest/, and never modifies canonical (intent-tree / intent-compass / packets), application code, target code, or the existing documents used as input (read-only. Canonical byte content is unchanged before and after execution. R4.1) - Keeps interpretation and candidate formation with the LLM; if an optional local read-only analysis or index is used, limits it to structural observation and recovery-basis collection and does not confirm intent from its output alone; falls back to direct code reading when analysis is unavailable, uninitialized, stale, or insufficient
- Reads the user-specified scope of existing code read-only and extracts intent candidates (roughly L0–L3), invariant candidates, and gaps of silence (places the code demonstrates but where no description of intent exists), writing them all out to
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.
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.
- 2mo ago First seen · 73 lines · 64 tokens per session scan A 9cc7702a5d87
intent-from-code is a skill published in the GitHub repository ijust/intent-planner (5 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 3,633 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 2026-08-31.
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Use when coordinating assignments, selected review boundaries, or blocked work across a rig.
oversight-team
Use when you are a seat on the oversight pod (a standing monitor-mode rig that keeps OTHER rigs healthy), configuring or running the drift detectors, or choosing whether to intervene vs escalate. Covers the pull-not-poll posture, the v0 detectors (premature-park, process-drift, off-task, token-burn), the intervention…