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 agentmods add skills/toejough/engram/openspec-update-changenpx skills add toejough/engram --skill openspec-update-changegit clone --depth 1 https://github.com/toejough/engramWrote 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/toejough/engram/openspec-update-change)<a href="https://agentmods.dev/skills/toejough/engram/openspec-update-change"><img src="https://agentmods.dev/badge/skills/toejough/engram/openspec-update-change.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.01307 |
| Opus 5 | $0.00028 | $0.00654 |
| Sonnet 5 | $0.00011 | $0.00261 |
| Haiku 4.5 | $0.00006 | $0.00131 |
Grade A, and why
openspec-update-change 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 4d 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.
This is a copy
70% identical to openspec-update-change — 38 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Revise a change's existing planning artifacts and keep them coherent. Never edit code.
Store selection: If the user names a store (a store is a standalone OpenSpec repo registered on this machine) or the work lives in one, run openspec store list --json to discover registered store ids, then pass --store <id> on the commands that read or write specs and changes (new change, status, instructions, list, show, validate, archive, doctor, context). Other commands do not take the flag. Hints printed by commands already carry the flag; keep it on follow-ups. Without a store, commands act on the nearest local openspec/ root.
Input: Optionally specify a change name. If omitted, check if it can be inferred from conversation context. If vague or ambiguous you MUST prompt for available changes.
Steps
-
If no change name provided, prompt for selection
Run
openspec list --jsonto get available changes sorted by most recently modified. Then use the AskUserQuestion tool to let the user select which change to update.Present the top 3-4 most recently modified changes as options, showing:
- Change name
- Schema (from
schemafield if present, otherwise "spec-driven") - Status (e.g., "0/5 tasks", "complete", "no tasks")
- How recently it was modified (from
lastModifiedfield)
Mark the most recently modified change as "(Recommended)" since it's likely what the user wants to update.
IMPORTANT: Do NOT guess or auto-select a change. Always let the user choose.
-
Get the change's artifacts
openspec status --change "<name>" --jsonParse the JSON to understand current state. The response includes:
schemaName: The workflow schema being used (e.g., "spec-driven")artifacts: Array of artifacts with their status ("done", "ready", "blocked")isComplete: Boolean indicating if all artifacts are completeplanningHome,changeRoot,artifactPaths, andactionContext: path and scope context. Use these instead of assuming repo-local paths.
The artifact ids and paths come from the active schema - do NOT assume them, and do NOT branch on hardcoded artifact names. Custom schemas must work unchanged.
The files to edit are
artifactPaths.<id>.existingOutputPaths- the concrete files that exist on disk, already glob-expanded for glob artifacts (e.g.specs/**/*.md). Do NOT write toresolvedOutputPath: for a glob artifact it is still the glob pattern, not a real file. -
Understand the request
- If the user asked for a specific revision ("the design now uses X"), that is the starting edit.
- If they only said "update" / "make this coherent", treat it as a coherence review: read the existing artifacts and check them against each other for contradictions, gaps, and duplication.
-
Read and reconcile
- Read the artifact(s) the request touches and the change's other existing artifacts.
- Apply the requested edit. Then check every other existing artifact against it - in ANY direction: an edit to a later artifact may require revising an earlier one, not only the other way around. Build order is a useful reading order, not a constraint on which artifacts may be revised.
- Note everything that is now inconsistent, missing, or contradictory.
- Revise only files that already exist (
existingOutputPaths). Do NOT create artifacts that don't exist yet, and do NOT invent new files under a glob artifact - note them and point the user to/opsx:continueto create them. - If the change is already coherent, say so and make no edits.
-
Confirm and apply, one artifact at a time
- Show each proposed revision and why. Write only after the user confirms.
- If the user rejects a revision, do not write it - leave that artifact unchanged.
- When a substantial rewrite is needed, get that artifact's rules and template first:
openspec instructions <artifact-id> --change "<name>" --json
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.
- 4d ago First seen · 87 lines · 55 tokens per session scan A 82a51ed50b10
openspec-update-change is a skill published in the GitHub repository toejough/engram (8 stars, last pushed 3d ago), licensed Apache-2.0. It adds 55 tokens to every session and 1,307 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 70% identical to openspec-update-change, differing in 38 lines, and is treated as a copy.
Other skills, from other repositories
langbot-mcp-ops
Operate a LangBot instance through its built-in MCP (Model Context Protocol) server. Use when an AI agent needs to manage LangBot — list/create/update/delete bots, pipelines, models, knowledge bases, MCP servers, and skills — over MCP instead of raw HTTP. Covers the /mcp endpoint, API-key auth (web-UI lbk keys and the…
browserwing-executor
Control browser automation through HTTP API. Supports page navigation, element interaction (click, type, select), data extraction, accessibility snapshot analysis, screenshot, JavaScript execution, and batch operations.
web-exfiltration-detection
Detect data exfiltration via URL path encoding and chained webfetch navigation. Covers fake trusted UI injection, letter-level URL path exfiltration, and multi-hop navigation hijacking. Use when the agent has web/URL fetch capability and stores user memory or personal context.
dev-browser
Browser automation with persistent page state. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website"…
memory-poisoning-detection
Detect persistent instruction injection or long-term memory poisoning. Focus on writing/retaining hostile instructions for future tasks, not data leakage.
harness-creator
Build, audit, and improve harnesses that make AI coding agents reliable: AGENTS.md/CLAUDE.md instruction files, feature/state tracking, verification gates, scope boundaries, session handoff, memory persistence, context budgets, tool-permission safety, and multi-agent coordination. Use this whenever a coding agent is…