study

A single procedure for processing content through Reliquery's stages: turning it into vault records, indexing it as searchable memory, and optionally updating its relationship graph.

In plain words
What is it for?
Processing a chapter, conversation, or other content so it becomes stored records, searchable memory, and—when appropriate—structured relationships.
Why use it?
It removes the need to know which individual stage to run or in what order, while skipping stages that have nothing new to process.

Skill for Claude CodeCodex

Part of the reliquery plugin — 6 skills, 1 MCP server shipped together

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/the-essential/reliquery/study
Any agent
npx skills add the-essential/reliquery --skill study
Clone the repo
git clone --depth 1 https://github.com/the-essential/reliquery

Made for: Claude Code, Codex.

Or install reliquery, the plugin that ships this one along with the rest of its 6 skills, 1 MCP server.

Per session 155 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,009 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 $0.00155 $0.02009
Opus 5 $0.00077 $0.01005
Sonnet 5 $0.00031 $0.00402
Haiku 4.5 $0.00015 $0.00201

Measured 3d ago against content hash 3e41b9899734, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

study 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 3d 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.

reliquery/skills/study/SKILL.md · 159 lines

How it starts

The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Identity

Study is the orchestrator — the master pipeline that chains chronicle, memorize, cartograph, and forget into a single coherent operation. Where the individual skills each handle one stage of the Reliquery lifecycle, study handles the intent: "I have content, and I want the system to learn it."

Study's disposition is efficiency without shortcuts. It moves through the pipeline briskly, collapsing unnecessary pauses between stages while preserving every checkpoint that protects the user's world. It recognizes when a step can be skipped (no new relics to index, KG already up to date) and says so rather than running empty phases. It recognizes when a step needs to be added (stale drawers that should be forgotten before re-indexing) and offers it seamlessly.

The user should never have to think about which skill to invoke or in what order. Study handles the routing.


How Study Works

Study operates in three stages that map to the underlying skills, with decision points between them that determine whether to continue, branch, or stop.

Content → [Chronicle] → Relics → [Memorize] → Drawers → [Cartograph offer] → KG
                                       ↑
                              [Forget if needed]

The user provides content and an intent. Study figures out the rest.


Stage 1 — Intake & Memory Check

Before invoking chronicle, study performs its own reconnaissance to understand what the system already knows and what's actually new.

1a — Load the palace

Call mempalace_status to confirm the system is live and identify the relevant wing.

1b — Scan the input

Read the user's provided content (manuscript excerpt, session log, conversation, scene draft) and identify every named entity: characters, factions, locations, systems, events.

1c — Memory check

For each identified entity, run dual lookups in parallel:

  • mempalace_search(query="[entity]", wing="[wing]") — what drawers exist
  • mempalace_kg_query(entity="[entity]") — what the KG knows

Read the full file on GitHub · 159 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.

  1. 3d ago First seen · 159 lines · 155 tokens per session scan A 3e41b9899734

Subscribe to this mod's changes

study is a skill published in the GitHub repository the-essential/reliquery (5 stars, last pushed 3mo ago), licensed MIT. It adds 155 tokens to every session and 2,009 once invoked, about $0.0008 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.

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