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/endogenai/dogma/workplan-scaffoldnpx skills add EndogenAI/dogma --skill workplan-scaffoldgit clone --depth 1 https://github.com/EndogenAI/dogmaWrote 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/endogenai/dogma/workplan-scaffold)<a href="https://agentmods.dev/skills/endogenai/dogma/workplan-scaffold"><img src="https://agentmods.dev/badge/skills/endogenai/dogma/workplan-scaffold.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 | $0.00104 | $0.02086 |
| Opus 5 | $0.00052 | $0.01043 |
| Sonnet 5 | $0.00021 | $0.00417 |
| Haiku 4.5 | $0.00010 | $0.00209 |
Grade A, and why
workplan-scaffold 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.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workplan Scaffold
This skill enacts the Algorithms Before Tokens axiom from MANIFESTO.md: the plan is encoded once as a committed document and referenced by every subsequent delegation — never re-derived from scratch mid-session. Workplan discipline is governed by AGENTS.md § Agent Communication → docs/plans/. When this skill and those documents conflict, the primary documents take precedence.
1. When to Create a Workplan
Create a workplan before executing any phase when the session meets one or more of these criteria:
| Criterion | Threshold |
|---|---|
| Number of phases | ≥ 3 |
| Number of agent delegations | ≥ 2 |
| Session spans multiple calendar days | Yes |
| Any change that renames or restructures committed files | Yes |
For single-phase, single-agent tasks with low risk, the scratchpad ## Session Start section is sufficient. The workplan is the plan of record; the scratchpad is live inter-agent memory.
2. Scaffold the Workplan
Use the scaffold script to create a correctly named, pre-filled workplan:
uv run python scripts/scaffold_workplan.py <brief-slug>
# Example:
uv run python scripts/scaffold_workplan.py add-research-skill
# Creates: docs/plans/2026-03-07-add-research-skill.md
Naming convention: docs/plans/YYYY-MM-DD-<brief-slug>.md — date-first for chronological sorting.
If the file already exists, the script exits with an error rather than overwriting. Use the existing file.
The canonical template is docs/plans/2026-03-06-formalize-workflows.md.
3. Required Workplan Structure
Every committed workplan must include the following sections:
# Workplan: <Title>
**Branch**: `<branch>`
**Date**: YYYY-MM-DD
**Orchestrator**: <Agent Name>
---
## Objective
<!-- One paragraph: what this session accomplishes and why -->
---
## Phase Plan
### Phase 1 — <Name> ⬜
**Agent**: <Agent Name>
**Deliverables**: <list>
**Depends on**: —
**Gate**: <acceptance test for this phase>
**Status**: ⬜ pending
### Phase 2 — <Name> ⬜
...
---
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 · 214 lines · 104 tokens per session scan A ffa0f575a7fc
workplan-scaffold is a skill published in the GitHub repository EndogenAI/dogma (2 stars, last pushed 11d ago), licensed Apache-2.0. It adds 104 tokens to every session and 2,086 once invoked, about $0.0005 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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