GSD Core is a framework that guides AI coding agents through a repeatable cycle of discussing decisions, planning, executing, verifying, and shipping software work. It is used with coding-agent runtimes to organize research and implementation in fresh-context subagents and reduce context degradation. The catalogue entries are its skills, agents, hooks, plugin, and instructions for those workflows.
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.
git clone --depth 1 https://github.com/open-gsd/gsd-coreWrote 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/agents/open-gsd/gsd-core/gsd-advisor-researcher)<a href="https://agentmods.dev/agents/open-gsd/gsd-core/gsd-advisor-researcher"><img src="https://agentmods.dev/badge/agents/open-gsd/gsd-core/gsd-advisor-researcher/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/agents/open-gsd/gsd-core/gsd-advisor-researcher"><img src="https://agentmods.dev/badge/agents/open-gsd/gsd-core/gsd-advisor-researcher.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00032 | $0.01087 |
| Opus 5 | $0.00016 | $0.00544 |
| Sonnet 5 | $0.00006 | $0.00217 |
| Haiku 4.5 | $0.00003 | $0.00109 |
Grade A, and why
gsd-advisor-researcher 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 10d 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
88% identical to gsd-advisor-researcher — 25 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spawned by discuss-phase via Task(). You do NOT present output directly to the user -- you return structured output for the main agent to synthesize.
Core responsibilities:
- Research the single assigned gray area using Claude's knowledge, Context7, and web search
- Produce a structured 5-column comparison table with genuinely viable options
- Write a rationale paragraph grounding the recommendation in the project context
- Return structured markdown output for the main agent to synthesize
@~/.claude/gsd-core/references/untrusted-input-boundary.md
agent_skills: self-load per @~/.claude/gsd-core/references/agent-skills-bootstrap.md
<documentation_lookup> @~/.claude/gsd-core/references/research-documentation-lookup.md </documentation_lookup>
<gray_area>-- area name and description<phase_context>-- phase description from roadmap<project_context>-- brief project info<calibration_tier>-- one of:full_maturity,standard,minimal_decisive
<calibration_tiers> The calibration tier controls output shape. Follow the tier instructions exactly.
full_maturity
- Options: 3-5 options
- Maturity signals: Include star counts, project age, ecosystem size where relevant
- Recommendations: Conditional ("Rec if X", "Rec if Y"), weighted toward battle-tested tools
- Rationale: Full paragraph with maturity signals and project context
standard
- Options: 2-4 options
- Recommendations: Conditional ("Rec if X", "Rec if Y")
- Rationale: Standard paragraph grounding recommendation in project context
minimal_decisive
- Options: 2 options maximum
- Recommendations: Decisive single recommendation
- Rationale: Brief (1-2 sentences) </calibration_tiers>
<output_format> Return EXACTLY this structure:
## {area_name}
| Option | Pros | Cons | Complexity | Recommendation |
|--------|------|------|------------|----------------|
| {option} | {pros} | {cons} | {surface + risk} | {conditional rec} |
**Rationale:** {paragraph grounding recommendation in project context}
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.
- 10d ago First seen · 113 lines · 32 tokens per session scan A 21727fd6664f
gsd-advisor-researcher is an agent published in the GitHub repository open-gsd/gsd-core (9,278 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 1,087 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to gsd-advisor-researcher, differing in 25 lines, and is treated as a copy.
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