Agent skill · Audited from source

Skill Management

skill · vellum-ai/vellum-assistantMIT licenceAudited 14 Oct 2026 · source 19bc86343b63

★ 1,425pushed 1 day ago
!CAUTIONGrade C · 79/100 · 11 findings · 19bc863
1,425repo stars · whole vellum-ai/vellum-assistant

Is it safe? With care — CAUTION, grade C (79/100). We read this skill's source at commit 19bc86343b63 and observed filesystem access and no hard-coded secrets. The audit raised 11 findings, 1 critical or high. What it does: Create, edit, and delete custom managed skills in the user's workspace. Use whenever the user wants to author a new skill from a description, scaffold a SKILL.md, or remove a skill they no longer need.

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Cite this page

ModelsAtlas. “Skill Management (vellum-ai/vellum-assistant)”. Retrieved 14 Oct 2026. https://modelsatlas.com/skills/vellum-ai/skill-management

Trust audit

Audit 0.4.1 · source read 14 Oct 2026

Trust score79/100!CAUTION C
0 critical1 high0 medium10 low0 info

CAUTION means the audit found things worth knowing before you trust this skill. Grade C is shared by 84 of 14,816 audited skills.

What the source does

  • FilesystemDeclared5 observations
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS5
L1 Static sourceSecrets, path traversal, supply chain, hidden codePASS5
L2 InstructionsPrompt injection, authority framing, hidden directivesFAIL1
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: instruction override, no behavioural pass.

Findings (11)

HIGHPrompt injectionprompt.hide_from_user · SKILL.md:128
F-01 Prompt injectionCWE-94 · CWE-1427Layer L2
> ⚠️ CRITICAL: Do not tell the user a skill is ready until you have confirmed it loads and activates on the intended trigger. A skill that was never loaded is a skill that was never tested. Never perf
Why
asks the agent to act without the user's knowledge
Fix
—
LOWFilesystem / pathfs.traversal · tools/delete-managed.ts:1
F-05 Filesystem / pathCWE-22 · CWE-59Layer L1
import { executeDeleteManagedSkill } from "../../../../tools/skills/delete-managed.js";
Why
No further detail recorded for this rule.
Fix
—
LOWFilesystem / pathfs.traversal · tools/delete-managed.ts:5
F-05 Filesystem / pathCWE-22 · CWE-59Layer L1
} from "../../../../tools/types.js";
Why
No further detail recorded for this rule.
Fix
—
LOWFilesystem / pathfs.traversal · tools/find-similar.ts:1
F-05 Filesystem / pathCWE-22 · CWE-59Layer L1
import { executeFindSimilarSkills } from "../../../../tools/skills/find-similar-skills.js";
Why
No further detail recorded for this rule.
Fix
—
LOWFilesystem / pathfs.traversal · tools/find-similar.ts:5
F-05 Filesystem / pathCWE-22 · CWE-59Layer L1
} from "../../../../tools/types.js";
Why
No further detail recorded for this rule.
Fix
—
LOWFilesystem / pathfs.traversal · tools/scaffold-managed.ts:1
F-05 Filesystem / pathCWE-22 · CWE-59Layer L1
import { executeScaffoldManagedSkill } from "../../../../tools/skills/scaffold-managed.js";
Why
No further detail recorded for this rule.
Fix
—

Audit 0.4.1 · source sha 19bc86343b63 · 14 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publishervellum-ai GitHub organizationOwner of the repository this skill is read from
  • Source foldervellum-ai/vellum-assistant/assistant/src/config/bundled-skills/skill-managementThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdict19bc86343b63A new audit runs when the source changes
  • Repository statusNot archivedLast push 1 day ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Create, edit, and delete custom managed skills in the user's workspace. Use whenever the user wants to author a new skill from a description, scaffold a SKILL.md, or remove a skill they no longer need.

---
name: skill-management
description: Create, edit, and delete custom managed skills in the user's workspace. Use whenever the user wants to author a new skill from a description, scaffold a SKILL.md, or remove a skill they no longer need.
metadata:
  emoji: "\U0001F9E9"
  vellum:
    display-name: "Skill Management"
    category: "system"
    activation-hints:
      - "User wants to scaffold a new managed skill in their workspace from a description"
      - "User wants to delete or list the custom skills they have defined"
      - "User wants to author or edit a SKILL.md and have it become invocable as a skill"
    avoid-when:
      - "User just wants to use an existing skill — that is normal skill activation, not management"
---

Manage the lifecycle of custom managed skills in `{workspaceDir}/skills`.

## When to Use

USE THIS SKILL WHEN:
- The user says "build me a skill" or "create a skill for X"
- The user wants to scaffold, edit, or delete a SKILL.md in their workspace
- The user wants a repeatable workflow captured as an invocable skill

Do NOT use this skill when the user just wants to run an existing skill. That is normal activation, not management.

## Capabilities

- **Scaffold** a new managed skill with YAML frontmatter and markdown body
- **Edit** an existing skill by scaffolding over it (replaces the body and needs `activation_hints` restated; every other frontmatter field you leave out keeps its current value, and an empty value clears one)
- **Delete** an existing managed skill directory

Skills created via `scaffold_managed_skill` become available for `skill_load` when a valid top-level `SKILL.md` is written under the skill directory.

## Step 1 - Align with the user before building

Ask before doing anything. Do not scaffold a skill until you have confirmed with the user:

- What the skill should do
- When it should activate (the trigger phrases, in their words)
- The major steps it performs
- Any destructive steps and the done condition

> ✓ Checkpoint: Have you confirmed scope with the user? If you are guessing at any of the four points above, ask first. Do not scaffold on assumption.

## Step 2 - Write a description AND activation-hints, always both

The description is what makes the skill discoverable. It must cover both what the skill does and when to reach for it, phrased the way the user would say it.

```yaml
description: Build anything visual — apps, landing pages, dashboards, trackers,
  calculators, games, tools, slide decks, or data visualizations. Use whenever
  the user wants something built that they can see and interact with.
```

**Every skill must also ship `activation-hints` in its frontmatter. This is not optional.** Keep `activation-hints` separate from the description: the description sells the skill, the hints list the concrete trigger phrases the user confirmed in Step 1.

```yaml
metadata:
  vellum:
    activation-hints:
      - "build me an app"
      - "make a dashboard"
      - "create a landing page"
```

> ✓ Checkpoint: Does the frontmatter have both a description and an `activation-hints` list? If hints are missing, go back and add them before writing the body.

## Step 3 - Structure the body so it survives weak models

Strong models tolerate loose structure. Weaker models drift. Build every body with these patterns.

**Open with a `## When to Use` block.** User language, not jargon. This is what makes the model recognize when the skill applies.

**Put critical warnings at the point of action.** A warning at the top of a file is forgotten by the time the model is 200 lines deep. Do not trust the top-of-file warning. Repeat the danger where the dangerous action happens.

```markdown
## Step 5 - Apply the JSON blob

⚠️ CRITICAL: Use the complete blob below. Setting even one key
wipes the entire block. Copy the whole thing or fail.
```

**Add explicit checkpoints between major steps, sparingly.** Long executions blur together. The model finishes step 3 and slides into step 4 without re-anchoring. A checkpoint forces a re-read. Use them between major sections, not on every step.

**Make branching explicit with `If / →`, and always name the default.** Prose hides decisions. The model reads linearly and walks past a branch without registering it. Every `If` must cover the default case. Implicit fall-through ("otherwise figure it out") creates drift.

```markdown
If the user already has a draft → restructure it into the template.
If not → build the steps from their description (default).
```

## Step 4 - Define done by binding tool calls to artifacts

Without an explicit done condition, the model invents one. It stops too early ("the file was created, done") or overshoots ("let me add one more feature"). Both are drift.

Each completion criterion must bind a **tool call** to the **user-visible artifact** it produces. Do not write criteria the model can satisfy by narration alone.

```markdown
## SKILL COMPLETE WHEN

- [ ] `scaffold_managed_skill` wrote the SKILL.md and returned its path
- [ ] User confirmed the skill loads via `skill_load`
- [ ] User saw the trigger phrases that will activate it
```

> ✓ Checkpoint: Before scaffolding, confirm the body has a `## When to Use` block, point-of-action warnings on any dangerous step, explicit `If / →` branches with named defaults, and artifact-bound completion criteria.

## Step 5 - Keep SKILL.md under 500 lines

Past 500 lines the model loses things in the middle. Warnings get buried, branching loses visibility, and the file fights the task for the same context budget. If a skill is growing past 500 lines, split reference material into separate files the skill points to.

Companion files ship through `scaffold_managed_skill`'s `files` input and live inside the skill folder:

- **`references/*.md`** for failure modes, gotchas, and cached values the body should point to.
- **`scripts/*`** for reusable code the procedure runs. Store the exact version that already ran successfully: pass `copy_from` wi

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 19bc863

Download folder ↗
git clone https://github.com/vellum-ai/vellum-assistant
git -C vellum-assistant checkout 19bc86343b63

The author documents no install command, so this uses the repository directly. Our verdict covers commit 19bc86343b63 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. !CAUTION C 79 / 100

    first audit · source 19bc86343b63

README badge

For maintainers · shows the latest audit

ModelsAtlas: CAUTION CMODELSATLASCAUTION · C
[![ModelsAtlas: CAUTION C](https://modelsatlas.com/skills/vellum-ai/skill-management/badge.svg)](https://modelsatlas.com/skills/vellum-ai/skill-management/)

The badge shows our verdict and grade for this skill, and links back to this page. It changes when the audit does.

Add this badge to your README

[![ModelsAtlas: CAUTION C](https://modelsatlas.com/skills/vellum-ai/skill-management/badge.svg)](https://modelsatlas.com/skills/vellum-ai/skill-management/)

Questions about Skill Management

What does the Skill Management skill do?
An AI Assistant that’s easy to setup, does your work 24/7, knows your preferences and gets better over time.
Is Skill Management safe to install?
With care. The audit graded it C (79/100) and found 11 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can Skill Management access on my machine?
The audit observed that it reads or writes files. Each of those is consistent with what it says it does. Secrets in the source: none found.
What do I need installed to use Skill Management?
Its own instructions reference activation_hints. Dependencies are pinned to exact versions.
How current is this page?
The grade is for one exact copy of the source (19bc86343b63), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

Sources

Spotted something wrong? Report a correction · Methodology

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