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 conorbronsdon/agent-workspace --skill endgit clone --depth 1 https://github.com/conorbronsdon/agent-workspaceWrote 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/conorbronsdon/agent-workspace/end)<a href="https://agentmods.dev/skills/conorbronsdon/agent-workspace/end"><img src="https://agentmods.dev/badge/skills/conorbronsdon/agent-workspace/end/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/conorbronsdon/agent-workspace/end"><img src="https://agentmods.dev/badge/skills/conorbronsdon/agent-workspace/end.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 | $0.00035 | $0.01489 |
| Opus 5.5 | $0.00014 | $0.00596 |
| Sonnet 5.5 | $0.00007 | $0.00298 |
| Haiku 4.5 | $0.00003 | $0.00149 |
Grade A, and why
end 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 1mo 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/end — Close Session
Capture the session and leave state ready for the next one: a session log, state updates, a decision-log append, memory proposals, and a git safety check.
Invocation: user-only (disable-model-invocation: true) — session close is timed by
you, and the flag keeps this skill out of ambient context.
Configuration
Read the optional workspace.yaml at the project root. Below, <state_dir> and
<sessions_dir> are its resolved values; defaults are state/ and sessions/. Full
reference: docs/state-model.md, including the Last Updated chain protocol and the
decision-log schema used in steps 3–4.
Instructions
-
Auto-extract session summary. Scan the full conversation and extract:
- Topics covered — what was worked on
- Decisions made — anything concluded or chosen, with rationale
- Rejected alternatives — for each meaningful decision, what else was considered and why it lost. If a bug was fixed, note the wrong theory tried first. If an approach changed mid-session, capture the pivot. This is the failed-hypothesis record that keeps a future session from repeating the same wrong starting point.
- State changes — priorities that shifted, threads that opened or closed
- Open threads — unfinished items or things waiting on someone
- Next actions — what needs to happen next session
Present the summary for quick confirmation before writing.
-
Write session log. Append to
<sessions_dir>/{TODAY}.md:## Session: {TIME} ### Topics - {topic} ### Decisions - {decision} ### Open Threads - {thread} ### Next Actions - {action} -
Update state files:
- Always update
current.md: add new threads, remove completed items, refresh timestamps on touched items. - Roll the
Last Updatedline throughcurrent-log.md(chain protocol). Keep exactly one**Last Updated:**line at the top ofcurrent.md, the newest. Never stack extra lines and never build a single-line "previous-entry" chain — that breaks the Read tool, breaksgrep, and splices parallel-session merges into single-line conflicts. Instead:- Read the existing
**Last Updated:**line fromcurrent.md. - Prepend it as its own line at the top of
<state_dir>/current-log.md, directly under the file header, newest first. Create the file with a# current.md update logheader if it does not exist. - Replace the
**Last Updated:**line incurrent.mdwith today's entry.
- Read the existing
- Always update
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.
- 1mo ago First seen · 133 lines · 35 tokens per session scan A 4a233fa38476
end is a skill published in the GitHub repository conorbronsdon/agent-workspace (2 stars, last pushed 26d ago), licensed MIT. It adds 35 tokens to every session and 1,489 once invoked, about $0.0001 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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source-command-github-github-modes
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source-command-github-github-swarm
Migrated source command github-github-swarm.
source-command-github-code-review
Migrated source command github-code-review.
git-conventions
Apply when committing, branching, or opening a pull request. Conventional commit format, branch naming, PR scope.
commit-history
List recent git commits linked to agent sessions, optionally filtered by branch or repo. Use when the user asks "show agent commits", "what has the agent shipped", "list linked commits", or wants commits with their session context.
Hooks Automation
Automated coordination, formatting, and learning from Codex operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.