The real dominant Linux failure, identified by a CCR Linux repro.
A CCR container reproduced the production signature — non-zero exit +
EMPTY stdout + EMPTY stderr (~60k fires/day, 4,485 Linux users on 2.0.4):
running `python -m venv` under a tight memory limit (ulimit -v) kills the
memory-heavy venv+ensurepip/pip subprocess with SIGSEGV (-11, RLIMIT_AS)
or SIGKILL (-9, kernel OOM-killer) BEFORE it writes anything. This is
NOT the ensurepip/packaging case (that always writes to stderr, code 11)
and NOT fixable by --target (a --target pip install is also memory-heavy
and gets killed too). Three earlier hypotheses (stdout, packaging,
Option A fixes Linux) were wrong — the repro corrected them.
Changes:
- Detect the signal kill (rc<0, or 128+sig: 134/137/139) in the venv/pip
and --target paths → err_kind "signal_killed:<rc>" (new code 16). The
returncode rides in a new sdk_bootstrap_rc metric so prod confirms
which signal dominates (-9 OOM-killer vs -11 RLIMIT_AS).
- Cooldown: on a signal kill, write a marker and return the new
SKIP_COOLDOWN outcome (9) on subsequent sessions for 24h — stops the
retry storm (every session was re-attempting a build that just gets
re-killed, burning the user's memory/CPU). Retries once per window so a
machine that frees memory still recovers.
- --no-cache-dir on both pip installs (venv + --target) trims pip's peak
memory; may get marginal machines under the OOM threshold.
No happy-path change: signal detection is at the top of the existing
failure handler; cooldown is checked only after all no-op probes
(NOOP_SYSTEM/VENV/TARGET short-circuit first).
Verified locally on macOS Python 3.13:
- py_compile clean.
- 35 new tests (test_signal_kill_cooldown.py): _is_signal_kill across
signals/exit-codes, rc decode, signal_killed→code 16, cooldown
lifecycle (none→write→expire), and an integration flow — simulated
SIGKILL'd venv → BUILD_FAILED/signal_killed:-9 + cooldown written →
2nd run SKIP_COOLDOWN without re-attempting → retry after window;
non-signal failure does NOT cool down; --no-cache-dir present on both
pip paths; sdk_bootstrap_rc emitted conditionally.
- End-to-end harness: the full kill→categorize→cooldown→skip→retry
chain confirmed in-process.
The original CCR repro (ulimit -v ≤7000 KB → rc=-11, empty streams) is
the ground truth this fix is built on. Can be re-validated on CCR with the
same ulimit approach.
Version 2.0.5 -> 2.0.6 per the per-PR-bump policy (#2114).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Option A, the data-gated fix for venv_ensurepip_fail (#2154 follow-up).
v2.0.4 telemetry made the call: of the venv_ensurepip_fail cohort, ~95%
HAVE pip (sdk_has_pip=true) and run Python 3.11–3.14 — so it's not the
Apple-3.9 problem; it's modern interpreters where `python -m venv` can't
bootstrap pip (Debian python3-venv absent, or python.org/pyenv builds
without ensurepip) but pip itself works. `pip install --target` needs only
pip, so it recovers the agentic reviewer for them instead of degrading to
pattern + single-shot review.
Producer (ensure_agent_sdk.py):
- New outcomes BUILT_TARGET=7, NOOP_TARGET=8; new phase pip_target=5.
- _build_via_target(): `pip install --target <state>/agent-sdk-libs
--upgrade --prefer-binary claude-agent-sdk`. Failures categorized via
_pip_err_from_stderr (sibling of main()'s pip chain — kept separate to
avoid disturbing the working venv categorizer); errno embedded for
OSError-family exceptions.
- _target_sdk_importable(): probes a prior target install → NOOP_TARGET.
Dir-check short-circuits before any subprocess, and it's only reached
when there's no working venv, so the 81% NOOP_VENV cohort never pays.
- main() falls through to the target build ONLY on venv_ensurepip_fail;
every other venv/pip failure stays terminal BUILD_FAILED. The sentinel
is released before the target build so a retry isn't seen as SKIP_SENTINEL.
Consumer (llm.py):
- _inject_agent_sdk_venv_into_syspath() adds the flat agent-sdk-libs dir
(packages sit directly in it, not under site-packages). The existing
pywin32 .pth bootstrap applies (target installs don't run .pth either).
No change to the happy path — the new branch is taken only on the
ensurepip failure, and the extra candidate dir is a no-op when absent.
Verified locally on macOS Python 3.13:
- py_compile clean.
- 30 new tests (test_venv_target_fallback.py): outcome/phase codes
(append-only, 4 stays retired), _pip_err_from_stderr categories,
_build_via_target success/CalledProcessError/timeout/exc+errno (mocked
subprocess), _target_sdk_importable dir-short-circuit, main() wiring
(ensurepip→target fallthrough + NOOP_TARGET probe + sentinel release),
consumer adds the flat dir. Full suite 533/533 pass + 2 skipped.
- END-TO-END harness (real install, simulated ensurepip failure):
main() → BUILT_TARGET, target dir has claude_agent_sdk; 2nd run →
NOOP_TARGET; consumer _inject → `import claude_agent_sdk` resolves
FROM the --target dir. Full chain proven without needing a
broken-ensurepip box.
- Real `pip install --target` + import confirmed independently (exit 0,
SDK imports from the flat layout).
NOT validated in tmux: the ensurepip failure can't be reproduced on macOS
(working ensurepip), so the fallback was proven via the real-install
harness above instead. The happy path (NOOP_VENV / normal agentic review)
is unchanged and covered by the existing hook-smoke suite.
Version 2.0.4 -> 2.0.5 per the per-PR-bump policy (#2114).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
assess only added SECRETS.local.md to analysis/.gitignore, leaving
*.local.patch uncovered until harden's own Step 0 ran. Both patterns are
now written by whichever command runs first.
A red-team pass found four ways credential values still reached
shareable artifacts after the initial redaction:
- the remediation patch: a diff removing a hardcoded secret carries the
raw value on its '-' lines by construction. harden now splits output:
non-credential hunks in the shareable security_remediation.patch,
credential hunks in a gitignored security_remediation.local.patch
with comment-only placeholders in the shareable file
- the other four agents had no secret-handling rules. legacy-analyst
(hardcoded-config evidence in tech-debt findings),
business-rules-extractor (credentials recorded as rule parameters),
test-engineer (legacy literals becoming committed test fixtures), and
architecture-critic (quoted code in notes files) now all mask values
and cite file:line; assess's tech-debt prompt and ASSESSMENT.md
masking now cover every section, not just Security Findings
- non-git projects: a .gitignore protects nothing under SVN/Mercurial.
Both commands now refuse --show-secrets without git and write the
quarantine file to ~/.modernize/<system>/ outside the project tree
- the patch-apply instruction was wrong in both documented layouts
(symlinked legacy/ broke relative paths). Patches are now written
with project-root-relative paths and applied from the project root
Also: --show-secrets is now position-independent in both commands, and
the README documents the full model.
Legacy systems often contain live credentials, and assessment/findings
files get committed and shared. Previously the security-auditor agent
reported hardcoded secrets verbatim into ASSESSMENT.md and
SECURITY_FINDINGS.md.
- security-auditor: mandatory secret-handling rules — mask all credential
values (file:line + 2-4 char preview), redact secrets from echoed tool
output, recommend rotation for anything that looks live
- assess/harden: gitignore-verified SECRETS.local.md quarantine file for
the per-credential inventory; findings files get masked entries and a
pointer only
- new --show-secrets flag opts into raw values in the quarantine file
(and only there)
- README: document the behavior and advise users of earlier versions to
check for already-committed findings and rotate
Follow-up to #2154. v2.0.3 telemetry showed the venv BUILD_FAILED bucket
splits into two unexplained groups; this PR instruments both.
## 1. The exc: bucket — exception type + errno
The dominant remaining venv BUILD_FAILED (phase=venv, err=99) is ~99%
sdk_bootstrap_stderr_sig=NULL — Python exceptions caught by the generic
`except Exception` ("exc:<TypeName>"), not CalledProcessErrors with
categorizable stderr. ~56k/30h, all opaque (stderr_sig only covers
"other:<tail>").
- Handler embeds errno for OSError-family: "exc:OSError:28", etc.
- SDK_BOOTSTRAP_EXC_CODES maps the type → sdk_bootstrap_exc
(FileNotFoundError=1 … OSError=6 … 99=other).
- errno decoded → sdk_bootstrap_errno (ENOENT/EACCES/ENOSPC/…).
## 2. venv_ensurepip_fail instrumentation (the other category)
venv_ensurepip_fail (code 11) is the top categorizable venv failure, and
telemetry flipped the naive assumption: it's NOT just Debian/Ubuntu —
macOS has the MOST distinct affected users (466 vs 121 linux), and linux
is a retry storm (~172 fires/user). Before committing to a `pip install
--target` fallback (Option A) we need to know (a) which interpreter these
users run and (b) whether that interpreter even has pip (→ whether
--target would work, vs needing a system package).
- sdk_hook_py (always emitted): interpreter version as major*100+minor
(309/312). Disambiguates Apple-3.9 vs a 3.10+-with-broken-ensurepip,
and also recovers the version for HOOK_PY_INCOMPATIBLE (whose "py_3.9"
err_kind otherwise collapses to err=99).
- sdk_has_pip (only on err==11, to avoid an extra subprocess per healthy
session): whether `<interpreter> -m pip --version` works. has_pip=true
→ the --target fallback would fix them; has_pip=false → they need a
system package (python3-venv / a complete Python).
Both #1 and #2 are purely additive telemetry on the existing BUILD_FAILED
path — no behavior change to the bootstrap. They de-risk the Option A
decision: ship A only if the affected cohort has pip.
Verified locally on macOS Python 3.13:
- py_compile clean.
- 39 tests in test_exc_failure_encoding.py (34 exc/errno + 5 ensurepip
instrumentation): type-code map, errno extraction + round-trip,
APPEND-ONLY stability, handler-embeds-errno, _probe_has_pip returns
bool + true-on-this-machine, sdk_hook_py always-emitted as
major*100+minor, sdk_has_pip gated on err==11.
- Full suite: 503/503 pass + 2 skipped.
Version 2.0.3 -> 2.0.4 per the per-PR-bump policy (#2114).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-04 14:55:55 -07:00
15 changed files with 862 additions and 146 deletions
"description":"Work with your Box content directly from Claude Code — search files, organize folders, collaborate with your team, and use Box AI to answer questions, summarize documents, and extract data without leaving your workflow.",
"description":"Build, iterate on, deploy, and manage Lovable apps from Claude Code. Bundles the official Lovable MCP server (remote, OAuth 2.1) and adds focused commands for the common build/iterate/database workflows, with credit- and publish-safety prompts.",
"author":{
"name":"Lovable"
},
"category":"development",
"source":{
"source":"url",
"url":"https://github.com/lovablelabs/mcp.git",
"sha":"9321737a737cf719db44c8124507f75e0bd0d270"
},
"homepage":"https://lovable.dev"
},
{
"name":"lua-lsp",
"description":"Lua language server for code intelligence",
"description":"Security review for Claude-generated code. Pattern-based warnings on edits, LLM-powered diff review on Stop, and an agentic commit reviewer that catches injection, XSS, SSRF, hardcoded secrets, and 25+ other vulnerability classes.",
@@ -29,6 +29,10 @@ The commands degrade gracefully, but each of these makes the output meaningfully
- **The whole system in the tree**: deployment descriptors (JCL, CICS definitions, route configs), copybooks/includes, and DDL/schemas. Entry-point detection and data lineage in `/modernize-map` are guesswork without them.
- **Production telemetry** (optional): an observability MCP server or batch job logs enable the runtime overlay in `/modernize-assess` and timing annotations on critical paths.
## Secret handling
Legacy systems routinely contain live credentials, and assessment artifacts get committed and shared. **Every agent in this plugin masks credential values** — findings, rule-card parameters, architecture notes, and test fixtures cite `file:line` with a masked preview (`AKIA****`), never the value. When credentials are found, a per-credential inventory (type, location, blast radius, rotation recommendation) is written to `analysis/<system>/SECRETS.local.md`, which the commands gitignore before writing; on non-git projects the quarantine file goes to `~/.modernize/<system>/` instead. `/modernize-harden` splits its remediation diff so credential-removal hunks (which necessarily contain the raw value) land in a gitignored `security_remediation.local.patch`, never the shareable patch. Pass `--show-secrets` to include raw values in the quarantine file (and only there). If you ran an earlier version of this plugin on a real system, check whether `analysis/` artifacts containing credentials were committed or shared, and rotate anything that was.
## Commands
The commands are designed to be run in order, but each produces a standalone artifact so you can stop, review, and resume.
description: Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
description: Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.
license: Complete terms in LICENSE.txt
---
This skill guides creation of distinctive, production-grade frontend interfaces that avoid generic "AI slop" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.
# Frontend Design
The user provides frontend requirements: a component, page, application, or interface to build. They may include context about the purpose, audience, or technical constraints.
Approach this as the design lead at a small studio known for giving every client a visual identity that could not be mistaken for anyone else's. This client has already rejected proposals that felt templated, and is paying for a distinctive point of view: make deliberate, opinionated choices about palette, typography, and layout that are specific to this brief, and take one real aesthetic risk you can justify.
## Design Thinking
## Ground it in the subject
Before coding, understand the context and commit to a BOLD aesthetic direction:
- **Purpose**: What problem does this interface solve? Who uses it?
- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction.
- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember?
If the brief does not pin down what the product or subject is, pin it yourself before designing: name one concrete subject, its audience, and the page's single job, and state your choice. If there's any information in your memory about the human's preferences, context about what they're building, or designs you've made before – use that as a hint. The subject's own world, its materials, instruments, artifacts, and vernacular, is where distinctive choices come from. Build with the brief's real content and subject matter throughout.
**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work - the key is intentionality, not intensity.
## Design principles
Then implement working code (HTML/CSS/JS, React, Vue, etc.) that is:
- Production-grade and functional
- Visually striking and memorable
- Cohesive with a clear aesthetic point-of-view
- Meticulously refined in every detail
For web designs, the hero is a thesis. Open with the most characteristic thing in the subject's world, in whatever form makes sense for it: a headline, an image, an animation, a live demo, an interactive moment. Be deliberate with your choice: a big number with a small label, supporting stats, and a gradient accent is the template answer, only use if that's truly the best option.
## Frontend Aesthetics Guidelines
Typography carries the personality of the page. Pair the display and body faces deliberately, not the same families you would reach for on any other project, and set a clear type scale with intentional weights, widths, and spacing. Make the type treatment itself a memorable part of the design, not a neutral delivery vehicle for the content.
Focus on:
- **Typography**: Choose fonts that are beautiful, unique, and interesting. Avoid generic fonts like Arial and Inter; opt instead for distinctive choices that elevate the frontend's aesthetics; unexpected, characterful font choices. Pair a distinctive display font with a refined body font.
- **Color & Theme**: Commit to a cohesive aesthetic. Use CSS variables for consistency. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.
- **Motion**: Use animations for effects and micro-interactions. Prioritize CSS-only solutions for HTML. Use Motion library for React when available. Focus on high-impact moments: one well-orchestrated page load with staggered reveals (animation-delay) creates more delight than scattered micro-interactions. Use scroll-triggering and hover states that surprise.
- **Spatial Composition**: Unexpected layouts. Asymmetry. Overlap. Diagonal flow. Grid-breaking elements. Generous negative space OR controlled density.
- **Backgrounds & Visual Details**: Create atmosphere and depth rather than defaulting to solid colors. Add contextual effects and textures that match the overall aesthetic. Apply creative forms like gradient meshes, noise textures, geometric patterns, layered transparencies, dramatic shadows, decorative borders, custom cursors, and grain overlays.
Structure is information. Structural devices, numbering, eyebrows, dividers, labels, should encode something true about the content, not decorate it. Many generic designs use numbered markers (01 / 02 / 03), but that's only appropriate if the content actually is a sequence - like a real process or a typed timeline where order carries information the reader needs. Question if choices like numbered markers actually make sense before incorporating them.
NEVER use generic AI-generated aesthetics like overused font families (Inter, Roboto, Arial, system fonts), cliched color schemes (particularly purple gradients on white backgrounds), predictable layouts and component patterns, and cookie-cutter design that lacks context-specific character.
Leverage motion deliberately. Think about where and if animation can serve the subject: a page-load sequence, a scroll-triggered reveal, hover micro-interactions, ambient atmosphere. An orchestrated moment usually lands harder than scattered effects; choose what the direction calls for. However, sometimes less is more, and extra animation contributes to the feeling that the design is AI-generated.
Interpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices (Space Grotesk, for example) across generations.
Match complexity to the vision. Maximalist directions need elaborate execution; minimal directions need precision in spacing, type, and detail. Elegance is executing the chosen vision well.
**IMPORTANT**: Match implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details. Elegance comes from executing the vision well.
Consider written content carefully. Often a design brief may not contain real content, and it's up to you to come up with copy. Copy can make a design feel as templated as the design itself. See the below section on writing for more guidance.
Remember: Claude is capable of extraordinary creative work. Don't hold back, show what can truly be created when thinking outside the box and committing fully to a distinctive vision.
## Process: brainstorm, explore, plan, critique, build, critique again
For calibration: AI-generated design right now clusters around three looks: (1) a warm cream background (near #F4F1EA) with a high-contrast serif display and a terracotta accent; (2) a near-black background with a single bright acid-green or vermilion accent; (3) a broadsheet-style layout with hairline rules, zero border-radius, and dense newspaper-like columns. All three are legitimate for some briefs, but they are defaults rather than choices, and they appear regardless of subject. Where the brief pins down a visual direction, follow it exactly — the brief's own words always win, including when it asks for one of these looks. Where it leaves an axis free, don't spend that freedom on one of these defaults. Just like a human designer who's hired, there's often a careful balance between doing what you're good at and taking each project as a chance to experiment and learn.
Work in two passes. First, brainstorm a short design plan based on the human's design brief: create a compact token system with color, type, layout, and signature. Color: describe the palette as 4–6 named hex values. Type: the typefaces for 2+ roles (a characterful display face that's used with restraint, a complementary body face, and a utility face for captions or data if needed). Layout: a layout concept, using one-sentence prose descriptions and ASCII wireframes to ideate and compare. Signature: the single unique element this page will be remembered by that embodies the brief in an appropriate way.
Then review that plan against the brief before building: if any part of it reads like the generic default you would produce for any similar page (work through a similar prompt to see if you arrive somewhere similar) rather than a choice made for this specific brief — revise that part, say what you changed and why. Only after you've confirmed the relative uniqueness of your design plan should you start to write the code, following the revised plan exactly and deriving every color and type decision from it.
When writing the code, be careful of structuring your CSS selector specificities. It's easy to generate CSS classes that cancel each other out (especially with a type-based selector like .section and a element-based selector like .cta). This can happen often with paddings/margins between sections.
Try to do a lot of this planning and iteration in your thinking, and only show ideas to the user when you have higher confidence it'll delight them.
## Restraint and self-critique
Spend your boldness in one place. Let the signature element be the one memorable thing, keep everything around it quiet and disciplined, and cut any decoration that does not serve the brief. Not taking a risk can be a risk itself! Build to a quality floor without announcing it: responsive down to mobile, visible keyboard focus, reduced motion respected. Critique your own work as you build, taking screenshots if your environment supports it – a picture is worth 1000 tokens. Consider Chanel's advice: before leaving the house, take a look in the mirror and remove one accessory. Human creators have memory and always try to do something new, so if you have a space to quickly jot down notes about what you've tried, it can help you in future passes.
## More on writing in design
Words appear in a design for one reason: to make it easier to understand, and therefore easier to use. They are design material, not decoration. Bring the same intentionality to copy that you would bring to spacing and color. Before writing anything, ask what the design needs to say, and how it can best be said to help the person navigate the experience.
Write from the end user's side of the screen. Name things by what people control and recognize, never by how the system is built. A person manages notifications, not webhook config. Describe what something does in plain terms rather than selling it. Being specific is always better than being clever.
Use active voice as default. A control should say exactly what happens when it's used: "Save changes," not "Submit." An action keeps the same name through the whole flow, so the button that says "Publish" produces a toast that says "Published." The vocabulary of an interface is the signposting for someone navigating the product. Cohesion and consistency are how people learn their way around.
Treat failure and emptiness as moments for direction, not mood. Explain what went wrong and how to fix it, in the interface's voice rather than a person's. Errors don't apologize, and they are never vague about what happened. An empty screen is an invitation to act.
Keep the register conversational and tuned: plain verbs, sentence case, no filler, with tone matched to the brand and the audience. Let each element do exactly one job. A label labels, an example demonstrates, and nothing quietly does double duty.
"description":"Security review for Claude-generated code. Pattern-based warnings on edits, LLM-powered diff review on Stop, and an agentic commit reviewer that catches injection, XSS, SSRF, hardcoded secrets, and 25+ other vulnerability classes.",
# `pip install --target` fallback (ensure_agent_sdk BUILT_TARGET, used
# when venv can't bootstrap pip): a FLAT layout — packages sit directly
# in agent-sdk-libs/, not under a site-packages subdir. See #2154
# follow-up. The pywin32 .pth bootstrap below applies here too (target
# installs don't process .pth at runtime, same as a manual venv insert).
+[os.path.join(state_dir,"agent-sdk-libs")]
)
added=False
forspincandidates:
Reference in New Issue
Block a user
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.
