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 thienanblog/awesome-ai-agent-skills --skill project-development-mindsetgit clone --depth 1 https://github.com/thienanblog/awesome-ai-agent-skillsWrote 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/thienanblog/awesome-ai-agent-skills/project-development-mindset)<a href="https://agentmods.dev/skills/thienanblog/awesome-ai-agent-skills/project-development-mindset"><img src="https://agentmods.dev/badge/skills/thienanblog/awesome-ai-agent-skills/project-development-mindset/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/thienanblog/awesome-ai-agent-skills/project-development-mindset"><img src="https://agentmods.dev/badge/skills/thienanblog/awesome-ai-agent-skills/project-development-mindset.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
SkillSpector: 1 finding, up to low
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- low Excessive Agency · line 20 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00038 | $0.00823 |
| Opus 5.5 | $0.00015 | $0.00329 |
| Sonnet 5.5 | $0.00008 | $0.00165 |
| Haiku 4.5 | $0.00004 | $0.00082 |
Grade A, and why
project-development-mindset 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 27d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Development Mindset
Deliver the requested outcome using project evidence and the smallest coherent change. Scale investigation and verification to impact, uncertainty, and reversibility.
Delegation
Run in the main conversation by default. Delegation can increase usage: obtain explicit approval for the proposed agent count and scope before using subagents. Reuse that approval within its bounds; ask again before expanding the approved count or scope.
Establish the task
- Inspect applicable instructions, Git state, and the source, tests, configuration, and docs relevant to the request. Preserve unrelated user work and follow the repository's branch and freshness policy.
- Identify observable success criteria and affected contracts. Plan in proportion to dependencies and uncertainty.
- Distinguish intended behavior from current behavior. Resolve stale or conflicting docs against source and runtime evidence; ask only when the remaining choice belongs to the user.
- Keep the original objective and accepted changes in view during long work. A status question or correction usually steers the task rather than replacing it.
Implement
- Reuse project components, dependencies, commands, and architecture when their semantics fit. Change a harmful pattern only where it affects this task.
- Keep abstractions tied to current invariants or meaningful reuse. Avoid speculative options, new frameworks, and adjacent cleanup without a present need.
- Inspect affected callers and consumers when changing public APIs, persisted data, permissions, or cross-project contracts.
- Use installed versions and official documentation for uncertain external APIs. Keep credentials out of source, logs, fixtures, and output.
- Carry authorized work through to completion. Prepare a concrete, reviewable result before requesting any still-missing approval for publication, deployment, or other consequential actions. Do not infer those actions from an ordinary implementation request.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 27d ago Changed · -1 lines · -3 tokens per session 56cc238082c4
- 1mo ago Changed · -149 lines · -35 tokens per session a81150bbd80e
- 1mo ago First seen · 200 lines · 76 tokens per session scan A b8cf615b6737
project-development-mindset is a skill published in the GitHub repository thienanblog/awesome-ai-agent-skills (70 stars, last pushed 27d ago), licensed Apache-2.0. It adds 38 tokens to every session and 823 once invoked, about $0.0002 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 2026-08-30.
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