context-steward

context-steward is a skill for Claude Code, Codex from DVNghiem/FlowDeck. It costs 46 tokens per session (2,756 once invoked), scanned A, original, MIT.

A context-management guide for keeping an AI coding session focused, by collecting, filtering, trimming, protecting, summarizing, and saving useful information.

In plain words
What is it for?
Use it to decide when to prune a crowded session, record context statistics, preserve important information, and save checkpoints before changing work phases.
Why use it?
Long tool results, loaded rules, failed attempts, and multiple agents can crowd the session and reduce response quality. It helps remove stale material while keeping user instructions and active work available.

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/dvnghiem/flowdeck/context-steward
Any agent
npx skills add DVNghiem/FlowDeck --skill context-steward
Clone the repo
git clone --depth 1 https://github.com/DVNghiem/FlowDeck

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.

agentmods badge for context-steward

README.md
[![agentmods](https://agentmods.dev/badge/skills/dvnghiem/flowdeck/context-steward.svg)](https://agentmods.dev/skills/dvnghiem/flowdeck/context-steward)
Your own site
<a href="https://agentmods.dev/skills/dvnghiem/flowdeck/context-steward"><img src="https://agentmods.dev/badge/skills/dvnghiem/flowdeck/context-steward.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,756 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 $0.00046 $0.02756
Opus 5 $0.00023 $0.01378
Sonnet 5 $0.00009 $0.00551
Haiku 4.5 $0.00005 $0.00276

Measured 5d ago against content hash f0962590c26e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

context-steward 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.

src/skills/context-steward/SKILL.md · 299 lines

How it starts

The opening of the file, as written. The whole thing — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Context Steward

FlowDeck sessions accumulate noise. Tool outputs, rule loads, failed attempts, and multi-agent chatter fill the context window. This skill defines a unified lifecycle to keep context lean, relevant, and recoverable.

When to Activate

Activate when:

  • Context exceeds 50% of the window and response quality drops
  • Multiple agents have contributed outputs in one session
  • Tool results are large (logs, diffs, file reads)
  • You are about to switch phases (plan → execute → verify)
  • A /fd-checkpoint is imminent

Core Principles

  • Context is a liability — every token not serving the current task is a distraction
  • Prune with purpose — never drop what the agent needs to continue
  • Protect the thread — user intent, active plans, and safety records are non-negotiable
  • Telemetry is cheap — write stats before pruning so patterns are visible later

Unified Context Lifecycle

1. Ingest

Everything that enters the session window:

Source Typical Size Risk Level
User prompts Small Low — never prune
Tool results (read, edit, bash) Variable High — can be huge
Skill loads Medium Medium — load once per session
Rule injections Small-Medium Medium — stage-gated already
Agent outputs Medium Medium — may contain plans or decisions
Memory queries Small Low
fdx-graph results Small-Medium Low

Ingest discipline: Before any large output enters context, ask whether it is needed for the next 5 turns. If not, summarize or redirect to file.


2. Filter

FlowDeck already gates rules by stage. Extend this discipline to all context sources.

Current Stage Load Defer / Skip
discuss Behavioral rules, AGENTS.md Coding standards, testing rules
plan Architecture rules, planning rules Security rules, lint rules
execute Coding standards, language patterns, security Debug rules (until needed)
verify Testing, security, linting rules Planning rules
fix-bug Debug, testing rules Architecture rules

Read the full file on GitHub · 299 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. 5d ago First seen · 299 lines · 46 tokens per session scan A f0962590c26e

Subscribe to this mod's changes

context-steward is a skill published in the GitHub repository DVNghiem/FlowDeck (24 stars, last pushed 16d ago), licensed MIT. It adds 46 tokens to every session and 2,756 once invoked, about $0.0002 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.

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