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Open Gsd/Gsd Profile User — measured AI agent skill | DecimalAI

open-gsd/gsd-profile-user

SkillScore57Maintained

Generate developer behavioral profile and create Claude-discoverable artifacts

by open-gsd

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

Personal Assistant pack

decimalai skills pull open-gsd-gsd-profile-user

Get this skill — curl · raw file

curl -fsSL https://app.decimal.ai/s/open-gsd-gsd-profile-user/SKILL.md

Raw file: /s/open-gsd-gsd-profile-user/SKILL.md ↗ · machine-readable summary at /s/open-gsd-gsd-profile-user.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

23 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 3d ago

—-36% tokens0% turns57% of whole cases pass with skill (13/23)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-17	✗→✓	▲ Improved	-67%	0%
case-04	✗→✓	▲ Improved	-38%	0%
case-06	✗→✓	▲ Improved	-17%	0%
case-08	✗→✓	▲ Improved	-21%	0%
case-09	✗→✓	▲ Improved	-46%	0%

Showing 5 of 23 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

open-gsd / gsd-core

skills/gsd-profile-user/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1

Skill contents

SKILL.md

<objective> Generate a developer behavioral profile from session analysis (or questionnaire) and produce artifacts (USER-PROFILE.md, gsd-dev-preferences skill config, CLAUDE.md section) that personalize Claude's responses.

Routes to the profile-user workflow which orchestrates the full flow: consent gate, session analysis or questionnaire fallback, profile generation, result display, and artifact selection. </objective>

<execution_context> @~/.claude/gsd-core/workflows/profile-user.md @~/.claude/gsd-core/references/ui-brand.md </execution_context>

<context> Flags from $ARGUMENTS:

--questionnaire -- Skip session analysis entirely, use questionnaire-only path
--refresh -- Rebuild profile even when one exists, backup old profile, show dimension diff

</context>

<process> Execute the profile-user workflow end-to-end.

The workflow handles all logic including:

Initialization and existing profile detection
Consent gate before session analysis
Session scanning and data sufficiency checks
Session analysis (profiler agent) or questionnaire fallback
Cross-project split resolution
Profile writing to USER-PROFILE.md
Result display with report card and highlights
Artifact selection (dev-preferences, CLAUDE.md sections)
Sequential artifact generation
Summary with refresh diff (if applicable)

</process>

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Other measured skills in the registry, with their headline benchmark lift.