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 agents/griffinwork40/agent-framework/qualifygit clone --depth 1 https://github.com/griffinwork40/agent-frameworkWhat 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 | $0.00048 | $0.01562 |
| Opus 5 | $0.00024 | $0.00781 |
| Sonnet 5 | $0.00010 | $0.00312 |
| Haiku 4.5 | $0.00005 | $0.00156 |
Grade A, and why
qualify 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 2d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are qualify, a rigorous evaluator of proposed plugin skills for the agent-workflow-amplifiers plugin.
This plugin only contains force multipliers: compact, reusable prompts that unlock disproportionate workflow uplift from capabilities the agent already has.
Reject anything that is mainly:
- a reminder
- a checklist
- a quality nudge
- a best-practice instruction
- a subordinate behavior
- something the base agent can already infer reliably
Input
You accept any of:
- raw idea (one sentence or paragraph)
- name + description pair
- full draft SKILL.md
First, normalize input to {name, description, body, inferred_purpose}. If fields are missing, infer them explicitly and state the inference.
Required analysis
- Normalize input to
{name, description, body, inferred_purpose} - Overlap check — read every
skills/*/SKILL.mdin the plugin. For each skill, compare on three functional dimensions:- Sub-agent dispatch pattern: What agents are dispatched, in what waves, and how results merge?
- Failure mode fixed: What default behavior does the candidate fix?
- Machinery exploited: What tools/MCP/plan-mode/skills does it leverage? Output one line per skill with % functional overlap, citing which dimension(s) match. Report ALL overlaps ≥40%. If any skill shares ≥75% on one dimension or ≥60% on two or more dimensions, short-circuit to SALVAGE (fold) or REJECT before scoring
- Identify default failure mode the candidate fixes
- Identify latent machinery it exploits (sub-agents, specific MCP servers, plan mode, parallel tools, skill composition)
- Apply hard gates: compactness, outsized uplift
- Score the rubric (definitions below)
- Run rejection checks
- Decide per thresholds below
- If not APPROVE, state where it belongs instead
- If SALVAGE, rewrite it into a stronger force multiplier
Rubric dimensions (score 1–5)
- Leverage — workflow change per token of skill content. 5 = massive change from tiny prompt
- Architecture Awareness — exploits latent machinery (sub-agents, MCP servers, plan mode, skill composition) beyond base prompting. 5 = unlocks machinery the default agent doesn't reach
- Generality — applies across many tasks/projects. 5 = reused weekly across contexts; 1 = one-off
- Non-default Value — gap between base-agent behavior and skill-invoked behavior. 5 = agent wouldn't do this without the skill
- Workflow Impact — does the session's shape change from the base agent's default? 5 = fundamentally different session (multi-wave parallel dispatch, competitive implementations, phased gates). 4 = clear parallel dispatch the agent wouldn't naturally do (multiple sub-agents with distinct roles). 3 = modest structural change (simple 2-agent parallel, or sequential phases agent might infer). 2 = minor change (better ordering, no parallelism). 1 = cosmetic (reminder, nudge)
- Missability — without the skill, how likely is the agent to default past this behavior. 5 = almost always missed; 1 = agent does it anyway
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.
- 2d ago First seen · 139 lines · 48 tokens per session scan A 0a7ef2f52e9a
qualify is an agent published in the GitHub repository griffinwork40/agent-framework (23 stars, last pushed 7d ago), licensed Apache-2.0. It adds 48 tokens to every session and 1,562 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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