* chore(stdlib): add conformance tooling for the skills library
The library had no gate that could express what a valid skill is, so
malformed frontmatter, over-budget files and credential literals went
unnoticed. These scripts define and enforce that contract.
- validate-skills.py: extend with Agent Skills v1.0 conformance -
naming rules and directory agreement, an explicit activation trigger
in the description, canonical layout, the 500-line SKILL.md budget,
relative-link integrity, and two security rules (no unrestricted
Bash(*) grant, no credential literals). Structural checks now read a
skill as a whole so material moved into references/ still counts.
- split-skill-references.py: move the heaviest sections of an oversized
SKILL.md into references/. Verifies line by line that every source
line lands in exactly one output and refuses to write otherwise.
- generate-skill-inventory.py: derive SKILLS_INVENTORY.md and
DIRECTORY_STRUCTURE.md from the tree so they cannot drift.
- generate-skill-catalog.py: index the canonical layout only, count
references/ toward a skill's size, and stop truncating descriptions
at 200 characters - the catalog is the discovery surface and must
carry the activation trigger.
- .gitignore: Python bytecode from these scripts, and local .pcl state.
Reviewed-by: Security Analyst, Compiler Engineer, DevX Engineer
* fix(stdlib): bring all 174 skills to Agent Skills v1.0 conformance
No skill in the library was conformant. 41 of 175 failed the existing
validator outright, and none satisfied the spec. This pass fixes the
tree and records the result. See stdlib/CHANGELOG.md for the per-skill
versioning and migration notes.
BREAKING CHANGE: one skill removed, five moved, seven with a capability
withdrawn. Library version 2.0.0 -> 3.0.0.
Structure
- Convert 71 skills stored as flat files to <category>/<name>/SKILL.md,
the layout the spec requires and the only one able to carry companion
resources.
- Rename 5 directories that disagreed with their declared name:, so
resolution by path and by name stop giving different answers. The
repository docs already referenced the corrected paths.
- Merge the duplicate legal-technology skills into legaltech-expert and
delete legal-tech-expert, carrying over everything the survivor
lacked.
Metadata
- Repair 20 unparseable frontmatters: an H1 preceded the --- block and
the key was skill_id: instead of name:, so any parser reading
frontmatter at offset 0 saw no metadata at all. The objectives,
prerequisites and outcome they carried become real body sections.
- Add the missing version: to 21 skills, fold keywords into tags, move
expertise_level under metadata, and align 10 category: values with
their directory.
Discoverability
- Give all 174 descriptions an explicit "Use when ..." trigger, built
from each skill's own tags and section headings. 152 previously said
only what the skill was about, leaving an agent nothing to match on.
Progressive disclosure
- Split 127 oversized skills, moving bulk material into references/ read
on demand and leaving an index behind. A SKILL.md now averages 277
lines instead of 644 and none exceeds 500. Verified lossless line by
line against the previous revision.
Security
- Withdraw the unrestricted Bash(*) grant from 7 skills; none of the six
non-financial ones contained a single shell command. finance-expert
documents code that charges cards and reads bank accounts, so it now
grants no shell at all.
- Remove credential literals: Stripe keys, two JWT signing keys, an
Express session secret, a Redis password and WiFi credentials, all
inlined in examples. They load from the environment now.
- finance-expert: idempotency keys were documented but absent, so a
retry double-charged; webhook signature failures were not caught, so a
forged event raised uncaught instead of being rejected;
int(amount * 100) truncated fractions of a cent. All fixed, plus a
money-movement guardrails section.
- trading-expert: place_order routed without any pre-trade risk check
although a RiskManager sat unused in the next section. Risk validation
now runs before routing and raises rather than returning a boolean a
caller can ignore; live routing is opt-in.
- Correct an Ansible Vault example that showed plaintext under an
"encrypted" label.
Also fixes 8 broken documentation links and a prematurely closed code
fence in skill-creator-expert that leaked template content into prose.
Per the repository file-organization policy, four stale progress reports
(SKILLS_MANIFEST, COMPLETE_SKILLS_LIBRARY, COMPLETE_LIBRARY_MANIFEST,
PHASE_3_DATA_ANALYTICS) move out of stdlib/ into the gitignored
.roadmap/status/stdlib/; they claimed 31 of 100 skills complete. They
appear here as deletions because .roadmap/ is not tracked.
Reviewed-by: Security Analyst, Language Designer, DevX Engineer,
Documentation Specialist
* fix(skills): resolve standard library skills from their real layout
No stdlib skill was resolvable. SkillResolver looked for
`<stdlibDir>/<name>.md` with stdlibDir defaulting to `stdlib/skills`, a
directory that does not exist, and the path ignored the category level
the library actually uses. The two LSP providers had the same wrong
directory and scanned only one level deep, so neither completion nor
go-to-definition could see a skill either.
- skill-discovery.ts: enumerate skill entry points across the shapes in
use - a flat `<name>.md`, `<name>/SKILL.md`, and
`<category>/<name>/SKILL.md` - while skipping references/, scripts/
and assets/, which hold supporting material rather than entry points.
- skill-resolver.ts: point stdlibDir at `stdlib`, and look the name up
as a directory under any category as well as the two legacy shapes, so
existing custom stdlib directories keep working. The name is used as a
single path segment and rejected if it contains a separator or
traversal, so a reference cannot escape the stdlib root.
- Rewire both LSP providers onto the shared discovery helper.
Tests: 13 new cases covering the layouts, ordering, the references/
exclusion, path-traversal rejection, and an integration test that
resolves real shipped skills by bare name.
Reviewed-by: Compiler Engineer, Runtime Architect, Security Analyst
* feat(stdlib): add 17 skills covering the library's largest gaps
Selection was driven by cross-referencing coverage against observed usage
rather than by intuition: Stack Overflow and GitHub Octoverse data for
which technologies matter, and install rankings on public agent-skill
registries for the shape of skills people actually use.
That comparison found a mismatch of form, not only of coverage. The
most-installed skills in the ecosystem are procedures - tdd, refactoring,
frontend design, browser automation - while all 174 existing skills were
domain knowledge shaped as <domain>-expert. The new workflows/ category
closes that gap and introduces the <activity>-workflow convention.
New category workflows/ (4)
- tdd-workflow, refactoring-workflow, debugging-workflow,
code-review-workflow. code-review-workflow complements rather than
replaces code-review-expert: procedure versus judgement. Merge them if
the split proves confusing in use.
Applied AI (3) - the largest coverage gap
- llm-engineering-expert, rag-expert, agent-engineering-expert.
The library referenced LLMs in tags but covered none of it: pgvector
appeared zero times across 174 skills, LangChain once, MCP twice
despite the repository shipping an MCP integration guide.
Capabilities (2)
- document-processing-expert (PDF, DOCX, XLSX, PPTX in one skill),
browser-automation-expert (a client against third-party sites,
distinct from playwright-expert which tests your own application).
Data (3)
- mysql-expert, the second most used database and previously absent
while rarer stores had skills; analytical-databases-expert;
stream-processing-expert.
Security (3)
- secrets-management-expert, supply-chain-security-expert (OWASP A03
2025), identity-access-expert (OWASP A01).
Interface and meta (2)
- accessibility-expert: design/ held only design-expert, which despite
its name covers software architecture, so WCAG had no home.
- skill-router: find and compose skills across 191, with a
disambiguation table for overlapping pairs.
Grouping by decision context rather than by technology keeps the growth
to 17 skills for roughly 50 topics. Five vector stores live inside
rag-expert; four document formats inside document-processing-expert.
Per-tool depth sits in references/, which the progressive-disclosure work
in 3.0.0 made cheap.
Four further gaps are better served by extending existing skills -
PyTorch and TensorFlow in ml-expert, OpenTelemetry in monitoring-expert,
Pulumi and Crossplane in terraform-expert - and are not in this change.
Library 3.0.0 -> 3.1.0, additive only. Adds the workflows label to the
inventory generator; catalogue, inventory, structure and CHANGELOG
regenerated.
Reviewed-by: Product Strategist, Security Analyst, DevX Engineer,
Documentation Specialist
* fix(test): create test directories with mkdtempSync
CodeQL flagged js/insecure-temporary-file (CWE-377) on both suites.
`join(tmpdir(), <predictable name>)` followed by mkdirSync creates a
world-readable directory at a guessable path, so another local user can
pre-create it or plant a symlink between the name being computed and the
directory being created.
mkdtempSync creates the directory atomically with a random suffix and
0700 permissions, which closes both the disclosure and the race.
One occurrence is new in this branch (skill-discovery); the other
pre-dates it in skill-resolver and is fixed in the same pass rather than
left as a known finding in a file this branch already touches.
11 KiB
name, version, description, category, tags, allowed-tools, metadata
| name | version | description | category | tags | allowed-tools | metadata | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| identity-access-expert | 1.0.0 | Design authentication and authorisation: OAuth 2.1 and OpenID Connect, session and token handling, RBAC and ABAC, and multi-tenant access control. Use when the user mentions OAuth, OIDC, SAML, SSO, JWT, refresh tokens, PKCE, login flows, sessions, roles and permissions, RBAC or ABAC, or when the task involves securing an API, implementing sign-in, or fixing a broken access control finding. | security |
|
|
|
Identity and Access Expert
Broken access control has been the top category in the OWASP Top 10 since 2021 and remains so in 2025. Most of it is not exotic: it is a check that exists at the route and not at the object.
Core Concepts
Authentication Is Not Authorisation
Authentication answers who is this. Authorisation answers may they do this to that. Conflating them produces the most common vulnerability in web applications: a logged-in user reading another user's records.
Check at the Object, Not Only the Route
# Vulnerable: authenticated, but any user can read any invoice (BOLA)
@router.get("/invoices/{invoice_id}")
async def get_invoice(invoice_id: str, user: User = Depends(current_user)):
return await repo.get(invoice_id)
# Correct: the query itself is scoped to what the caller may see
@router.get("/invoices/{invoice_id}")
async def get_invoice(invoice_id: str, user: User = Depends(current_user)):
invoice = await repo.get_for_tenant(invoice_id, tenant_id=user.tenant_id)
if invoice is None:
raise HTTPException(404) # not 403: do not confirm existence
return invoice
Scoping the query rather than fetching and then comparing is what makes this robust: there is no path where a developer forgets the comparison.
Tokens Are Bearer Credentials
Whoever holds the token is the user. Design accordingly: short lifetimes,
transport only over TLS, never in a URL, never in localStorage for
session-bearing tokens, and revocable.
OAuth 2.1 and OIDC
OAuth 2.1 consolidates current practice: PKCE is mandatory for all clients, the implicit and password grants are removed, and redirect URIs must match exactly.
| Flow | Use |
|---|---|
| Authorisation code + PKCE | All interactive clients — web, SPA, mobile, desktop |
| Client credentials | Service to service, no user |
| Device code | Input-constrained devices |
| Refresh token (rotating) | Extending a session without re-authentication |
OIDC adds identity on top: an id_token describing who authenticated. The
access token is for calling APIs; the id token is for your application to learn
the user's identity. Never send an id token as an API credential.
# Authorisation request with PKCE
verifier = secrets.token_urlsafe(64)
challenge = base64.urlsafe_b64encode(
hashlib.sha256(verifier.encode()).digest()
).rstrip(b"=").decode()
params = {
"response_type": "code",
"client_id": CLIENT_ID,
"redirect_uri": REDIRECT_URI, # must match the registered value exactly
"scope": "openid profile invoices:read",
"state": state, # CSRF protection, bound to the session
"nonce": nonce, # replay protection, checked in the id_token
"code_challenge": challenge,
"code_challenge_method": "S256",
}
On callback, verify state against the session before anything else, then
exchange the code with the verifier. A missing state check is an account
takeover via CSRF on the login endpoint.
Validating a JWT
Most JWT vulnerabilities come from validating too little.
import jwt
from jwt import PyJWKClient
jwks = PyJWKClient(f"{ISSUER}/.well-known/jwks.json", cache_keys=True)
def verify(token: str) -> dict:
key = jwks.get_signing_key_from_jwt(token).key
return jwt.decode(
token,
key,
algorithms=["RS256"], # allowlist; never read alg from the header
issuer=ISSUER, # must match
audience=AUDIENCE, # must match: a token for another API is invalid
options={
"require": ["exp", "iat", "iss", "aud", "sub"],
"verify_exp": True,
"verify_signature": True,
},
leeway=30, # clock skew, not a grace period
)
The failures this prevents, all seen in the wild:
alg: none— accepting an unsigned token. Fixed by the algorithm allowlist.- Algorithm confusion — an RS256 public key used as an HS256 shared secret. Same fix.
- Missing audience check — a valid token issued for a different service is accepted.
- Missing issuer check — a token from any issuer with a valid signature.
- Decoding without verifying —
jwt.decode(..., options={"verify_signature": False})in production code.
Fetch JWKS over TLS, cache with a TTL, and handle key rotation by refreshing on
an unknown kid rather than pinning a key.
Sessions Versus Tokens
| Server session | Stateless JWT | |
|---|---|---|
| Revocation | Immediate | Not until expiry, without extra state |
| Scale | Needs shared store | No lookup |
| Size | Small cookie | Larger, sent on every request |
| Claims freshness | Always current | Stale until refresh |
For first-party web applications, server-side sessions in a cookie are usually the better choice: revocation works, and the cookie flags do the heavy lifting.
response.set_cookie(
"session",
session_id,
httponly=True, # not readable by JavaScript
secure=True, # TLS only
samesite="lax", # CSRF mitigation; "strict" if no cross-site entry points
max_age=8 * 3600,
path="/",
domain=None, # host-only: do not widen to a parent domain
)
Use short-lived access tokens with rotating refresh tokens where statelessness is required. Rotation with reuse detection turns a stolen refresh token into a detectable event:
async def refresh(presented: str) -> TokenPair:
record = await store.get(hash_token(presented))
if record is None:
raise Unauthorised()
if record.used:
# This token was already exchanged - it was stolen and replayed.
await store.revoke_family(record.family_id)
alert("refresh token reuse", family=record.family_id, user=record.user_id)
raise Unauthorised()
await store.mark_used(record.id)
return await issue_pair(record.user_id, family_id=record.family_id)
Authorisation Models
RBAC — permissions attach to roles, roles to users. Simple, auditable, and sufficient for most applications.
ABAC — decisions evaluate attributes of subject, resource, action and context. Necessary when rules depend on data: ownership, department, time, location, amount.
ReBAC — decisions follow relationships in a graph. Fits document sharing and hierarchical resources where "can view because they can view the parent folder" is the rule.
Most systems need RBAC for coarse capability plus ownership checks for the rest. Reach for a policy engine when the rules genuinely warrant it.
@dataclass(frozen=True)
class Decision:
allowed: bool
reason: str = ""
def authorise(user: User, action: str, resource: Resource) -> Decision:
if action not in ROLE_PERMISSIONS.get(user.role, ()):
return Decision(False, f"role {user.role} lacks {action}")
if resource.tenant_id != user.tenant_id:
return Decision(False, "cross-tenant access")
if action.startswith("invoice:approve") and resource.amount_minor > user.approval_limit_minor:
return Decision(False, "above approval limit")
return Decision(True)
Keep the decision in one place, return a reason, and log denials. Scattering
if user.role == "admin" through the codebase makes the policy unknowable and
unreviewable.
Multi-Tenancy
Tenant isolation is the highest-severity boundary in a SaaS application.
# Bind the tenant at the session boundary, not per query
@contextmanager
def tenant_scope(session, tenant_id: str):
session.execute(text("SET LOCAL app.tenant_id = :t"), {"t": tenant_id})
yield session
-- The database enforces it, so a forgotten WHERE cannot leak
ALTER TABLE invoices ENABLE ROW LEVEL SECURITY;
CREATE POLICY tenant_isolation ON invoices
USING (tenant_id = current_setting('app.tenant_id')::uuid);
Defence in depth: scope in the query, enforce at the database, and write a test that asserts a request authenticated as tenant A returns nothing belonging to tenant B. Test it for every resource type, not once.
Best Practices
- Deny by default. An endpoint with no explicit policy must reject.
- Authorise at every layer, including internal service calls. A service mesh does not know your object model.
- Use a vetted identity provider. Implementing OIDC from scratch is a large, ongoing security liability.
- Short access tokens (5–15 minutes), rotating refresh tokens with reuse detection.
- MFA for privileged operations, with phishing-resistant factors (WebAuthn) for administrators.
- Re-authenticate for sensitive actions — changing an email, adding a payout destination.
- Audit authorisation decisions: actor, action, resource, outcome, reason.
- Return 404 rather than 403 where existence itself is sensitive.
- Rate limit and lock out on authentication, with a delay that does not reveal whether the account exists.
Anti-Patterns
- Route-level checks only — the BOLA pattern, and the most exploited flaw in APIs.
- Trusting a client-supplied identifier for the tenant or user.
algread from the token header.- Long-lived tokens with no revocation path.
- Session tokens in
localStorage— readable by any XSS. - Role checks scattered through handlers — unauditable.
- Hiding UI as authorisation — the API is the boundary.
- Rolling your own crypto or your own SSO.
- Different error messages for unknown user and wrong password — user enumeration.
Reference Documentation
- Implementation Patterns — complete OIDC integration, API gateway authorisation, service-to-service auth, policy engines, and migration from legacy authentication