What is imladris-deliberate?

A skill for asking several independent AI models to examine a difficult question, then organizing their agreement, disagreements, missing coverage, and distinct ideas. Imladris is the local service that coordinates this discussion.

Use it to compare technical options, review an architecture, investigate a research question, critique an answer, or continue a discussion with the same group of models.

It reduces the risk of relying on one model for research, design choices, comparisons, or critiques where mistakes matter.

How FeanorsCodeSL/imladris configures Claude Code and Codex

Reuse

Borrowing it

Nothing to install: this file belongs to FeanorsCodeSL/imladris. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/FeanorsCodeSL/imladris/main/.agents/skills/imladris-deliberate/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/FeanorsCodeSL/imladris

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/feanorscodesl/imladris/imladris-deliberate/github.svg)](https://agentmods.dev/skills/feanorscodesl/imladris/imladris-deliberate)

Your own site

<a href="https://agentmods.dev/skills/feanorscodesl/imladris/imladris-deliberate"><img src="https://agentmods.dev/badge/skills/feanorscodesl/imladris/imladris-deliberate/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/feanorscodesl/imladris/imladris-deliberate"><img src="https://agentmods.dev/badge/skills/feanorscodesl/imladris/imladris-deliberate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 864 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00089	$0.00864
Opus 5.5	$0.00036	$0.00346
Sonnet 5.5	$0.00018	$0.00173
Haiku 4.5	$0.00009	$0.00086

Measured 2mo ago against content hash 071d94182f64, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

imladris-deliberate 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.

.agents/skills/imladris-deliberate/SKILL.md · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Imladris Deliberation

When to use

Reach for Imladris when a task is hard enough that one model's answer is risky: research questions, design/architecture trade-offs, "compare X and Y", expert critique, or anything where being wrong is costly. For quick lookups, answer directly — deliberation costs ~N panel calls + an analysis call.

Quick Start

Imladris is an MCP stdio server — there is no HTTP endpoint, port, or token. Your harness spawns imladris-mcp; call its tools directly. The /council prompt wraps the one-shot flow below. Use /council-session when the user wants a sustained back-and-forth with the same council.

Call the imladris tool:

prompt (required), context (optional extra context for every panellist)
preset or panel — which of your configured providers answer
analysis_model — override which provider runs the analysis judge
thread_id — present means session mode; Imladris reads/writes the local ~/.imladris/sessions/<thread_id>.json file and reconstructs messages[]
prior_answer — in session mode, pass your previously authored answer for this thread so Imladris can store it as the assistant turn

Inspect configuration and health with imladris_status (resolved roster, roles, presets, budget thresholds, budget estimates — never secrets or env-var names). Clear local session files with imladris_clear_sessions.

Workflow

If meta.ok == 0, every panellist failed and the tool returns a clean meta.failure — say so instead of inventing evidence; let the harness fall back.
Send the user's question as prompt. Add context for files/constraints.
Pick a preset (your configured presets — use a local-only preset when the data must not leave the network) or an explicit panel.
You are the final author. Read the analysis — especially blind_spots and contradictions — and the raw_answers, then write the answer, preserving genuine disagreements and caveats rather than smoothing them away.
For a session, use the same thread_id on each turn and pass your last answer as prior_answer. If the host drops it, Imladris backfills from stored analysis.
When the analysis flags a claim as low-confidence, verify it before relying on it.

Read the full file on GitHub · 62 lines

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.

2mo ago First seen · 62 lines · 89 tokens per session scan A 071d94182f64

Subscribe to this mod's changes

imladris-deliberate is a skill published in the GitHub repository FeanorsCodeSL/imladris (4 stars, last pushed 4mo ago), licensed MIT. It adds 89 tokens to every session and 864 once invoked, about $0.0004 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.

Building agents

imladris-deliberate next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
imladris-deliberateFeanorsCodeSL/imladris	Skill	4	4mo ago	MIT	A	89	Claude Code, Codex
imagegenopenai/codex	Skill	134k	today	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	today	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	today	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	314k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	today	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	today	MIT	A	103	Claude Code

imladris: Skill for Claude Code